Apify vs Context.dev
usage-based · credits · subscription-flat · free-tier · marketplace-rev-share
·free-tier · usage-based
Context.dev wins · 21–23 (50 drawn)
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
Agent access
ai-native userPoint an agent at llms.txt or agent-oriented docs
weight 2 · round drawnA direct probe confirms llms.txt is live at docs.apify.com/llms.txt returning HTTP 200 with structured agent-oriented documentation content, and the docs also expose an OpenAPI spec and dedicated MCP integration docs for agent discovery. Missing for 10: independent third-party confirmation that agents successfully consume/parse the llms.txt in practice.
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.apify.com/llms.txt # Apify Documentation > Apify is the largest marketplace of tools for AI. Thous…”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
- [claimed-docs] “Discover and use Actors with AI agents and LLMs via Apify MCP server.”
Context.dev has a confirmed live llms.txt at docs.context.dev/llms.txt (HTTP 200, agent-oriented index of docs), plus agent-oriented docs, MCP server, CLI, and a coding-agent skill install guide, directly enabling an agent to be pointed at agent-native documentation. Missing for 10: independent third-party confirmation that agents successfully consume the llms.txt in practice beyond the probe check.
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.context.dev/llms.txt # Context.dev - [The go-to web data API](https://docs.context.dev/introductio…”
- [claimed-docs] “Connect your AI client to Context.dev tools for live web and company data.”
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
- [claimed-docs] “Teach your coding agent how to choose and use the Context.dev API.”
- [probe] “official MCP server documented at https://mcp.context.dev/mcp”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
ai-native userRun the product headlessly / in CI for automation
weight 2 · round drawnApify provides a CLI for scripting/terminal control (apify-docs-3, apify-probe-4), scheduling for automated runs (apify-docs-6), an OpenAPI-backed REST API (apify-probe-2), and Actors designed as headless automation units runnable via SDKs/CLI, all consistent with CI/headless automation use. missing for 10: explicit CI/CD pipeline integration examples (e.g., GitHub Actions) or independent hands-on confirmation of CI usage.
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [claimed-docs] “Develop your own Actor”
Context.dev ships a CLI explicitly documented for scripting and CI use ('Call Context.dev from your terminal and use JSON responses in scripts or CI'), backed by a full REST API with OpenAPI spec, async batch jobs for long-running headless crawls, and documented rate-limit/timeout handling suited to automated pipelines. Missing for 10: no explicit CI/CD pipeline example (e.g., GitHub Actions), and no independent/community confirmation of headless CI usage beyond vendor docs.
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “`return-partial` | Return usable completed work with a completion marker. If no usable result exists, fail without a charge.”
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
ai-native userConnect an agent via an official MCP server
weight 3 · round drawnApify documents an official MCP server enabling AI agents/LLMs to discover and use Actors, confirmed both in docs and a direct probe of the dedicated MCP integration page. Missing for 10: independent/hands-on third-party corroboration of the MCP server working in practice.
- [claimed-docs] “Discover and use Actors with AI agents and LLMs via Apify MCP server.”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
Context.dev is a web-data API (not itself an agent), so the MCP-server axis applies, and it publishes an official hosted MCP endpoint (mcp.context.dev/mcp) plus install docs for connecting AI clients to its tools for live web/company data. Missing for 10: independent/hands-on verification of the MCP server working in practice beyond first-party docs and a probe confirming the endpoint exists.
- [probe] “official MCP server documented at https://mcp.context.dev/mcp”
- [claimed-docs] “Connect your AI client to Context.dev tools for live web and company data.”
ai-native userUse an official CLI
weight 2 · round to ApifyApify ships an official CLI (apify-cli) documented at docs.apify.com/cli, explicitly described as a tool to "Control the Apify platform from terminal or shell scripts," covering Actor development, deployment, and automation workflows relevant to AI-native/agentic use. missing for 10: independent hands-on community validation specifically of CLI usage (comments reference SDK/product broadly, not CLI specifics).
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Develop your own Actor”
Docs and probe confirm an official CLI exists ('Call Context.dev from your terminal and use JSON responses in scripts or CI') with a dedicated install page, supporting agentic/CI workflows. However, there's no independent/hands-on corroboration of the CLI's functionality or depth beyond first-party docs. Missing for 10: independent verification/hands-on review of CLI usage, details on CLI command coverage vs the full API surface.
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
ai-native userDrive the product through a documented public API
weight 3 · round drawnApify provides a documented public REST API with an OpenAPI spec (verified live at docs.apify.com/api/openapi.json), plus a CLI for scripting the platform and official docs describing programmatic control, giving AI-native users clear, verifiable ways to drive the product via API. Missing for 10: independent third-party corroboration of API robustness/completeness beyond Apify's own docs and probes.
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [claimed-docs] “Develop your own Actor”
Context.dev is fundamentally an API product with a public OpenAPI spec, documented endpoints (crawl, extract, screenshot, brand data, auth), API key management, rate-limit headers, plus a CLI and MCP server built on top of the same API — clear evidence of a documented, drivable public API for AI-native consumption. Missing for 10: independent third-party developer confirmation of full API coverage beyond docs/probes.
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Choose **Restricted** when an integration needs only selected operations; a restricted key with no permissions cannot call the API.”
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
- [claimed-docs] “discover → register → deliver setup link & code to the user → user completes claim in browser → poll for access_token → call API.”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
ai-native userIssue scoped/least-privilege API credentials for an agent
weight 2 · round to Context.devApifynone0/10No evidence of scoped or least-privilege API token/credential issuance for agents—docs mention permissions management for organizations and MCP integration but nothing about granular/scoped API keys or credential minimization for agent use.
Docs explicitly describe restricted API keys scoped to selected operations only, with a no-permission key unable to call the API at all, directly supporting least-privilege credential issuance for agents; the OAuth-like device flow (discover→register→claim→poll) also supports scoped token issuance per client. missing for 10: no evidence of fine-grained scoping beyond operation-level (e.g., resource/data scoping), and no independent/hands-on confirmation of restricted-key behavior in production.
- [claimed-docs] “Choose **Restricted** when an integration needs only selected operations; a restricted key with no permissions cannot call the API.”
- [claimed-docs] “discover → register → deliver setup link & code to the user → user completes claim in browser → poll for access_token → call API.”
ai-native userBuild against official SDKs
weight 2 · round to ApifyApify offers official SDKs for JavaScript/Python plus Crawlee, documented developer toolkits, a CLI, an OpenAPI spec, and an MCP server enabling AI agents to build against official interfaces, with community corroboration of SDK adoption. Missing for 10: deeper independent benchmarking of SDK quality/completeness beyond community praise and more explicit versioned SDK reference docs in the pack.
- [claimed-docs] “Software toolkits for developing new Actors.”
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [community] “I'm a huge fan of Apify and look forward to exploring this new SDK. Thanks y'all.”
Context.devnone0/10The evidence shows an OpenAPI spec, CLI, MCP server, and 'skill' for coding agents, but there is no mention of official SDK client libraries (e.g., Python, JS, Go packages) for Context.dev. Missing for 10: explicit official SDK packages/documentation, language-specific client libraries, versioning/release notes for SDKs.
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
ai-native userSubscribe to events via webhooks
weight 2 · round to Context.devApifynone0/10The evidence pack never mentions webhooks explicitly; only vague references to alerts and monitoring (apify-docs-7) exist, with no documentation of webhook subscription or event triggers. Missing for 10: any docs on webhook creation, event types, subscription API, or delivery guarantees.
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
Context.dev supports monitoring pages/sitemaps/datasets and receiving 'signed change events' on a schedule, which functions as a webhook-like event delivery mechanism, but the docs never explicitly describe a subscribe/webhook API, event types, delivery retries, or webhook management endpoints. missing for 10: explicit webhook subscription/management API docs, event schema/type documentation, delivery reliability/retry details, and independent confirmation of webhook functionality.
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
Agentic features
ai-native userGet AI-generated insights and suggestions from my data inside the product
weight 2 · round drawnApifynone0/10Evidence covers Actor development, monitoring/alerts, MCP server for AI agents to use Actors, and CLI/API access — but nothing shows the product itself generating AI insights or suggestions from a user's scraped/collected data. Missing for 10: any feature describing AI-generated summaries, insights, or recommendations derived from data collected in Apify.
Context.devnone0/10Context.dev is a data-extraction/scraping API (Markdown, structured JSON extraction, screenshots, brand data) intended to feed external AI agents and applications, but there is no evidence of the product itself surfacing AI-generated insights, recommendations, or analysis inside a Context.dev interface — it delivers raw/structured data, not in-product AI insight generation.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “retrieve brand profiles with logos, colors, descriptions, and social links through the same API.”
- [claimed-docs] “Connect your AI client to Context.dev tools for live web and company data.”
ai-native userSet up automations that run autonomously in the background
weight 2 · round to ApifyApify supports scheduling Actors/tasks to run automatically at specific times, plus monitoring and alerting for background runs, and a CLI/API for orchestration—covering autonomous background automation. Missing for 10: independent hands-on validation of scheduling reliability and no explicit mention of event/webhook-triggered (vs. time-triggered) autonomous runs.
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Context.dev supports background automation via async batch crawling that runs as a tracked job until completion, and scheduled monitoring of pages/sitemaps/datasets that emits signed change events without user intervention — both run autonomously once configured. However, there's no evidence of a broader automation/workflow engine (e.g., chaining actions, triggering downstream agent tasks, retries/orchestration) beyond these two specific background job types. Missing for 10: evidence of workflow chaining or agent-triggered automation, independent confirmation of monitoring reliability, and details on scheduling flexibility.
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
ai-native userDelegate tasks to a built-in AI assistant inside the product
weight 3 · round drawnApifynone0/10Evidence shows Apify exposes an MCP server so external AI agents can call Apify's Actors, but there is no mention of a built-in AI assistant inside the Apify product itself that users can delegate tasks to.
- [claimed-docs] “Discover and use Actors with AI agents and LLMs via Apify MCP server.”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
ai-native userOperate the product with natural-language commands
weight 2 · round drawnApify documents an official MCP server enabling AI agents/LLMs to discover and invoke Actors via natural-language-driven agent tooling, which is the core mechanism for natural-language operation, plus an llms.txt for AI discoverability. However, there's no direct evidence of a natural-language interface within Apify's own console/CLI itself (the CLI is a traditional command-line tool, not NL-driven), so operation relies on pairing with an external agent. Missing for 10: first-party natural-language chat/assistant interface in the platform itself, hands-on demonstration of NL commands working end-to-end via MCP, independent corroboration of MCP usability.
- [claimed-docs] “Discover and use Actors with AI agents and LLMs via Apify MCP server.”
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.apify.com/llms.txt # Apify Documentation > Apify is the largest marketplace of tools for AI. Thous…”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Context.dev ships an official MCP server ('Connect your AI client to Context.dev tools for live web and company data') and an agent 'skill' file that teaches coding agents how to call the API, which together let AI-native users issue natural-language requests that get translated into API calls; there is also a CLI for scripted/terminal use. However, all natural-language operation is mediated through third-party AI clients (Claude, agents) rather than a native NL interface in Context.dev itself, and no community/hands-on evidence confirms this NL workflow works smoothly in practice. Missing for 10: first-party or independent evidence of actual natural-language usage/output quality via the MCP or skill integration, and any native chat/NL interface within the product itself.
- [claimed-docs] “Connect your AI client to Context.dev tools for live web and company data.”
- [claimed-docs] “Teach your coding agent how to choose and use the Context.dev API.”
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
- [probe] “official MCP server documented at https://mcp.context.dev/mcp”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
ai-native userApply a preset configuration tuned for research agents that returns structured, citable output
weight 2 · round drawnApifynone0/10No evidence of a preset configuration tuned for research agents that yields structured, citable output; Apify's evidence covers general Actor development, MCP server access, CLI, and marketplace but nothing about a research-agent-specific preset or citation-formatted output.
Context.devnone0/10Context.dev is a web scraping/data extraction API with structured extraction, crawling, and monitoring features, but there is no evidence of a preset or configuration profile specifically tuned for 'research agents' that returns structured, citable output (e.g., with source attribution/citations). The extraction guide supports JSON Schema output but nothing about citation tracking or a research-agent preset.
Api quality
ai-native userExplore an interactive API reference with runnable examples
weight 2 · round to ApifyApify publishes an OpenAPI spec (confirmed live at docs.apify.com/api/openapi.json) which underlies an API reference, and general docs exist, but there's no direct evidence of an interactive reference UI with runnable/try-it examples (e.g., a Swagger/Redoc try-it console) being confirmed. Missing for 10: explicit evidence of an interactive 'try it out' console, runnable code snippets in the API reference, or community confirmation of using such a feature.
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [claimed-docs] “Develop your own Actor”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
Context.devnone0/10Evidence confirms docs, guides, and an OpenAPI spec exist, but nothing indicates an interactive reference with runnable/try-it-out examples (no Swagger/Redoc playground, no 'try it' feature mentioned).
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)
weight 2 · round drawnA probe confirms a valid OpenAPI spec is publicly downloadable at docs.apify.com/api/openapi.json, and this is complemented by official CLI and MCP integration docs enabling machine-driven access. Missing for 10: independent third-party confirmation of spec completeness/versioning beyond the probe.
A probe confirms a live OpenAPI JSON spec at docs.context.dev/openapi.json (HTTP 200, contains 'openapi' key), directly satisfying the machine-readable spec requirement, alongside first-party docs describing the API surface. Missing for 10: independent third-party corroboration of spec completeness/versioning beyond the probe check.
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
ai-native userTest against a sandbox environment without touching production data
weight 1 · round drawnApifynone0/10No evidence pack items mention a sandbox environment, staging mode, or separation from production data for testing Actors; docs cover development, CLI, MCP, scheduling, monitoring but nothing about a sandbox/test environment isolated from production data.
ai-native userRely on versioned APIs with a documented deprecation policy
weight 2 · round drawnApifynone0/10Evidence shows Apify has an OpenAPI spec, docs, CLI, and MCP server, but nothing indicates a documented API versioning scheme or a deprecation policy for breaking changes. Missing for 10: explicit API version numbers/paths, a published deprecation/sunset policy, changelog or migration guidance for breaking changes.
data-engineerThe documented rate limit (requests per second or minute) enforced on my API key before throttling kicks in
weight 3 · round to Context.devApifynone0/10No evidence pack item documents specific rate-limit numbers (requests per second/minute) for the Apify API; only general docs, CLI, MCP, and community sentiment are present, with no mention of throttling thresholds per API key.
Docs confirm a per-minute rate limit exists and that authenticated responses expose rate-limit headers, but no specific numeric threshold (requests/sec or /min) is given in the evidence. Missing for 10: the actual documented numeric limit value, guidance on limits per plan/key tier, and confirmation via headers example showing remaining/limit values.
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
Anti bot — getting past bot defenses — CAPTCHAs, fingerprinting, blocksAnti bot
Getting past bot defenses — CAPTCHAs, fingerprinting, blocks
Block evasion
ai-native userHave an agent automatically get past a CAPTCHA, login, or form wall without my manual intervention
weight 2 · round drawnApifynone0/10Apify's evidence covers proxy rotation to avoid IP-based blocking (apify-docs-8) and general Actor/browser automation tooling, but nothing documents automatic CAPTCHA solving, login handling, or form-wall bypass as a built-in capability. Missing for 10: any explicit CAPTCHA-solving feature, documented login/session automation, or evidence of autonomous form-wall bypass without user intervention.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
Context.devnone0/10Context.dev is a web scraping/crawling/data-extraction API; there is no evidence of CAPTCHA-solving, login/session automation, or form-wall bypass capability. Community comments even question its handling of restricted/anti-scraping sites, and no docs describe login or CAPTCHA handling.
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “\"Websites can opt out of our service, and we respect these requests and add them to our block list.\" I.e: robots.txt already exists and is…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
data-engineerAutomatically retry through a chain of different proxies when anti-bot detection blocks a request
weight 2 · round to ApifyApify documents smart proxy rotation across datacenter and residential IPs to avoid blocking, which supports proxy chaining, but there's no explicit evidence of an automated retry mechanism that specifically triggers on anti-bot detection and cycles through proxies as a chain. missing for 10: documented automatic retry logic tied to anti-bot/block detection, evidence of configurable retry chains, independent confirmation of this workflow in practice.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
Context.devnone0/10No documentation or evidence describes proxy rotation, proxy-chain retries, or anti-bot bypass mechanisms; a community comment explicitly notes the homepage never mentions IP rotation or residential proxies, reinforcing the absence of this capability.
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
developerUse an undetected browser mode to bypass sophisticated bot detection systems
weight 3 · round drawnApifynone0/10Evidence shows IP rotation/proxy features and browser automation library support (Playwright, Puppeteer, Selenium), but no mention of a specific 'undetected browser' mode or stealth fingerprinting/anti-bot-detection bypass capability.
Context.devnone0/10No evidence in the pack claims an 'undetected browser' or anti-bot-bypass mode; the docs describe scraping, crawling, screenshots, and browser actions but never mention stealth/anti-detection techniques, and community comments explicitly question whether the product uses rotating/residential IPs at all, suggesting no such capability is documented.
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
Proxy rotation
developerRequest a proxy from a specific country to get geolocation-appropriate content
weight 2 · round to ApifyApify's docs mention proxy rotation to avoid blocking (datacenter and residential IPs) but the evidence pack does not explicitly confirm country-specific/geolocation targeting for proxies. missing for 10: explicit documentation of country-level proxy selection parameters, independent confirmation of geo-targeting accuracy.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
Context.devnone0/10No documentation or feature mentions country-specific proxy selection or geolocation control; community comments even question whether Context.dev uses rotating/residential proxies at all, suggesting no such capability exists.
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
developerUse premium residential or datacenter proxies to bypass sites that are hard to scrape
weight 3 · round to ApifyApify docs explicitly describe smart rotation of datacenter and residential IP addresses to avoid blocking, directly matching the anti-bot proxy use case, and the platform's marketplace/integration docs corroborate a mature proxy infrastructure. missing for 10: no independent hands-on benchmark or third-party report validating residential proxy success rates against specific hard-to-scrape sites.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Marketplace of 64,279 Actors”
Context.devnone0/10No documentation or product page mentions residential/datacenter proxies, IP rotation, or anti-bot bypass infrastructure; community comments explicitly note the absence of any proxy mention and question whether the product can handle high-value/anti-scraping targets like LinkedIn.
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
developerRoute requests through a rotating pool of proxy IPs to avoid blocks
weight 3 · round to ApifyApify explicitly documents proxy rotation across datacenter and residential IPs to avoid blocking, directly matching the story. Missing for 10: independent/hands-on corroboration of proxy rotation effectiveness and details on configuration/pricing tiers.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
Context.devnone0/10No documentation or product page mentions proxy IP rotation, residential proxies, or anti-blocking infrastructure; a community comment on Hacker News explicitly notes the homepage never mentions 'ip' and questions whether rotating/residential proxies are used at all.
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
developerRoute multiple requests through the same proxy IP using a session identifier to maintain a consistent identity
weight 2 · round drawnApifynone0/10The evidence only shows generic proxy IP rotation (apify-docs-8) but contains no mention of session identifiers, sticky sessions, or maintaining a consistent IP across multiple requests, which is the specific capability the story requires.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
Context.devnone0/10No documentation or product page mentions session-based IP persistence, sticky sessions, or proxy identity management; the crawl/scrape/extract guides only cover content retrieval, not proxy control. A community comment even flags the total absence of any IP/residential-proxy discussion on the site, reinforcing that this capability isn't offered.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
ai-native userPerform bulk operations across many items at once
weight 2 · round drawnApify's platform supports running Actors at scale (marketplace of 64k Actors, CLI/API/SDK for scripting, scheduling, proxy rotation), which implies bulk automation across many items/tasks, and the API/OpenAPI + CLI enable programmatic bulk control. However, there's no explicit documentation or example of a bulk-operations API (e.g., batch-running many Actors/items in one call) or dataset-level bulk processing tailored for AI-native usage. missing for 10: explicit bulk/batch API documentation, dataset-scale bulk operation examples, independent verification of bulk performance at scale.
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Marketplace of 64,279 Actors”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Docs describe genuine bulk capability: async crawl jobs processing up to 25,000 pages in the background with progress tracking, plus a smaller 500-page synchronous crawl mode, which cover bulk operations across many web pages. However, evidence doesn't show bulk operations across arbitrary item sets (e.g., batch brand lookups, batch document parsing, or bulk extraction across a list of disparate items) beyond website crawling, and there's no independent/hands-on corroboration of large-scale batch reliability. Missing for 10: evidence of bulk/batch endpoints beyond crawling (e.g., batch document conversion, batch structured extraction across arbitrary item lists), and third-party validation of large-scale batch performance.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
ai-native userDefine rules that trigger actions automatically on events
weight 3 · round drawnApify docs show automatic scheduling of Actors/tasks at specific times and performance alerts, which are limited forms of automated triggers, but the evidence pack lacks explicit documentation of a general event-driven rule/webhook system that fires actions on arbitrary platform events (e.g., dataset changes, run status) as an AI-native user would define. Missing for 10: explicit webhook/event-trigger API docs, examples of custom event-condition-action rules, and independent confirmation of event-based (not just time-based) automation.
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
Context.dev supports watching a page, sitemap, or dataset on a schedule and receiving signed change events, which functions as an event-trigger mechanism, but this is presented as a single monitoring feature rather than a general rule-definition system with configurable conditions and varied actions. Missing for 10: evidence of a rules/conditions engine, multiple trigger types beyond scheduled monitoring, and configurable downstream actions (e.g., webhooks to arbitrary endpoints, multi-step workflows).
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
ai-native userSchedule recurring jobs or workflows
weight 2 · round to ApifyApify's docs explicitly support scheduling Actors and saved tasks to run automatically at specific times (recurring jobs), plus CLI and API access for programmatic control, fitting AI-native automation workflows. missing for 10: independent hands-on confirmation of scheduling reliability and richer detail on cron-like configuration options.
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
The docs describe a monitoring feature that watches a page, sitemap, or dataset 'on a schedule' and emits signed change events (context-dev-docs-9), which is a form of recurring job scheduling, but this is scoped only to change-detection, not general recurring crawl/extract/workflow jobs. Missing for 10: evidence of cron-style scheduling for arbitrary crawl/extract jobs, workflow chaining, or a broader job-scheduling API beyond the single 'monitor' feature.
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
Dev experience — day-to-day developer experience — setup friction, docs, debugging, iteration speedDev experience
Day-to-day developer experience — setup friction, docs, debugging, iteration speed
Collaboration
developerShare scrapers with teammates and manage organizations and role-based permissions
weight 2 · round to ApifyApify's official docs explicitly mention sharing Actors and managing organizations/permissions, directly matching the story, but the evidence pack only has a single doc title with no detail on role granularity or workflow, and no independent/hands-on corroboration of this feature. Missing for 10: detailed documentation of role-based permission levels, screenshots/hands-on walkthrough, and community confirmation that org/permission management works well in practice.
- [claimed-docs] “Share Actors with other people, manage your organizations and permissions.”
Context.devnone0/10No evidence of team/organization features, shared scraper workflows, or role-based permission management beyond restricted API keys, which is a single-key scoping mechanism, not team/org collaboration. Missing for 10: organization/team creation, member invites, role-based access control across users, shared scraper/workflow assets.
- [claimed-docs] “Choose **Restricted** when an integration needs only selected operations; a restricted key with no permissions cannot call the API.”
Deployment flexibility
developerBuild and deploy custom serverless scraping scripts on the platform without managing my own infrastructure
weight 2 · round to ApifyApify's core value proposition is building 'Actors' (custom scraping scripts) deployed serverlessly on their platform, with docs covering development toolkits, SDKs (JS/Python), CLI for terminal control, scheduling, monitoring, and migration guides for existing projects. Community feedback corroborates real-world usage of the platform for custom scraping projects without infrastructure management. Missing for 10: independent hands-on benchmarks of deployment ease/scaling limits, and more recent community validation beyond older HN threads.
- [claimed-docs] “Develop your own Actor”
- [claimed-docs] “Software toolkits for developing new Actors.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Learn how to easily move your existing projects to the Apify platform.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [community] “I've used Apifier a lot of times and is the best of all the similar products in the market (or at least the other 4 (?) I've tried).”
- [community] “I'm a huge fan of Apify and look forward to exploring this new SDK. Thanks y'all.”
Context.devnone0/10Context.dev exposes a fixed set of hosted scraping endpoints (crawl, extract, screenshot, monitor, parse) accessed via API/CLI/MCP, but there is no evidence of a mechanism for developers to write and deploy their own custom scraping scripts or actors on the platform's infrastructure. This is a fair question for a web-scraping-as-a-service category, so absence of evidence yields 'none' rather than 'na'.
developerDeploy the scraping service via a Docker container for production use
weight 2 · round drawnApifynone0/10None of the evidence explicitly mentions Docker or containerized deployment for Apify Actors; docs reference generic Actor development, toolkits, CLI, and migration guides but never state Docker-based deployment. Missing for 10: explicit Docker/Dockerfile documentation, container registry or image-based deployment workflow, and any hands-on confirmation of Docker usage for production scraping.
developerSelf-host an open-source version of the scraper instead of relying on a hosted cloud service
weight 2 · round drawnApifynone0/10Apify's evidence shows CLI tooling and local Actor development (apify-docs-3, apify-probe-4), but nothing indicates a fully self-hostable open-source version of the platform as an alternative to the hosted cloud service — Apify's core value proposition remains the managed cloud platform and marketplace. missing for 10: evidence of an open-source self-hosted runtime/platform replacing the cloud service, docs on self-hosting infrastructure, community confirmation of running Apify independently of apify.com.
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Context.devnone0/10No evidence anywhere in the pack of an open-source or self-hostable version of Context.dev; it is presented exclusively as a hosted cloud API/service with CLI, MCP server, and SDKs pointing to context.dev endpoints. Missing for 10: any open-source repo, self-hosting instructions, Docker image, or license permitting local deployment.
Integrations
developerConnect the scraping API to no-code automation platforms like n8n or Zapier through a prebuilt connector
weight 2 · round drawnApifynone0/10No evidence in the pack mentions n8n, Zapier, or any prebuilt no-code automation connector; the docs reference MCP server, CLI, SDKs, and Actor Store but nothing about a no-code platform integration.
Library compatibility
developerBuild scrapers using popular open-source automation libraries like Playwright, Puppeteer, Selenium, or Scrapy
weight 2 · round to ApifyApify explicitly states it works with Playwright, Puppeteer, Selenium, and Scrapy alongside its own Crawlee library, and docs cover Actor development toolkits and migrating existing projects onto the platform. Missing for 10: hands-on independent verification/tutorials specifically showing Selenium or Scrapy actors running end-to-end, and community evidence is thin/tangential on this specific capability.
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Develop your own Actor”
- [claimed-docs] “Software toolkits for developing new Actors.”
- [claimed-docs] “Learn how to easily move your existing projects to the Apify platform.”
Migration lock in
developerExport my scraped data and job configurations in a portable format to migrate to another provider without lock-in
weight 3 · round drawnApifynone0/10Evidence shows Apify's CLI, API, and docs for migrating projects INTO Apify (apify-docs-11) but nothing about exporting scraped data or job configurations in a portable format to move AWAY from Apify to another provider; Actors/tasks are platform-specific constructs with no documented export-for-migration path.
- [claimed-docs] “Learn how to easily move your existing projects to the Apify platform.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
Quickstart
developerPublish my custom scraper to a public marketplace and earn revenue when others use it
weight 1 · round to ApifyApify explicitly documents publishing Actors to the public Apify Store for 'regular passive income' and has a marketplace of 64k+ Actors, directly matching the story. Missing for 10: independent third-party confirmation of actual developer earnings/payouts and details on revenue-share terms.
- [claimed-docs] “Publish your Actors on Apify Store and earn regular passive income.”
- [claimed-docs] “Marketplace of 64,279 Actors”
- [claimed-docs] “Share Actors with other people, manage your organizations and permissions.”
developerRun a ready-made scraper from a marketplace instead of building one from scratch
weight 2 · round to ApifyApify Store offers a marketplace of 64,279 ready-made Actors (scrapers) that developers can run directly instead of building from scratch, backed by docs on publishing/sharing Actors and the llms.txt description confirming it as 'the largest marketplace of tools for AI' with 'thousands of ready-made Actors'. Community reviews corroborate real-world usage of pre-built scrapers as a core value proposition. Missing for 10: no hands-on walkthrough evidence of actually running a marketplace Actor end-to-end or independent review specifically praising the marketplace-run experience.
- [claimed-docs] “Publish your Actors on Apify Store and earn regular passive income.”
- [claimed-docs] “Share Actors with other people, manage your organizations and permissions.”
- [claimed-docs] “Marketplace of 64,279 Actors”
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.apify.com/llms.txt # Apify Documentation > Apify is the largest marketplace of tools for AI. Thous…”
- [community] “I've used Apifier a lot of times and is the best of all the similar products in the market (or at least the other 4 (?) I've tried).”
Context.devnone0/10Context.dev's evidence describes a general-purpose scraping/crawling/extraction API, CLI, and MCP server that developers configure themselves, but no marketplace of pre-built, ready-made scrapers for specific sites/use-cases is mentioned anywhere in the docs, community discussion, or probes.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
developerStart building immediately using a library of ready-made project templates
weight 1 · round to ApifyApify provides a CLI and 'software toolkits for developing new Actors' plus a large marketplace of 64,279 pre-built Actors, which functionally lets developers start from existing building blocks, but the evidence never explicitly documents a curated 'project template' gallery or scaffolding command with named starter templates. Missing for 10: explicit template gallery/documentation, CLI scaffolding command details (e.g., 'apify create' template list), independent confirmation of ease-of-start experience.
- [claimed-docs] “Software toolkits for developing new Actors.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Marketplace of 64,279 Actors”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Extraction quality — how faithfully content is extracted — structure, fidelity, edge casesExtraction quality
How faithfully content is extracted — structure, fidelity, edge cases
Ai extraction
developerExtract structured data from a page using natural language instructions instead of writing selectors
weight 3 · round to Context.devApifynone0/10No evidence of a natural-language-to-extraction feature; Apify's documented capabilities center on Actors, crawlers, CLI, MCP integration and marketplace, not AI-driven selector-free extraction from prompts.
Docs describe an extract endpoint that crawls relevant pages and returns an object matching a JSON Schema with controls for grounding, coverage, and freshness—no CSS/XPath selectors required, just a schema/instructions-driven approach. Missing for 10: no explicit mention of natural-language instruction fields (vs. schema-only), no independent hands-on benchmark of extraction accuracy/quality.
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “retrieve brand profiles with logos, colors, descriptions, and social links through the same API.”
developerPass a JSON schema so the API returns structured data matching that schema
weight 2 · round to Context.devApifynone0/10No evidence pack item describes passing a JSON schema to constrain/validate API output structure for extraction; docs cover Actor development, CLI, MCP server, and general platform features but nothing about schema-guided structured output.
Docs explicitly describe extracting structured data by supplying a JSON Schema, with the API returning an object matching it, plus controls for grounding, coverage, and freshness; an OpenAPI spec is also available for verification. Missing for 10: independent hands-on confirmation of schema-conformance accuracy and no explicit mention of schema validation/error handling edge cases.
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
ai-native userHave an LLM read a page and decide what structured fields to pull out without pre-written selectors
weight 2 · round to Context.devApifynone0/10Evidence shows Apify's marketplace, CLI, MCP server, and Actor platform, but nothing about an LLM-driven extraction mode that reads a page and decides structured fields without pre-written selectors — no AI-extraction Actor or feature is documented.
The extract-structured-data guide shows the product accepts a JSON Schema and returns matching structured data with grounding/coverage controls, which fits an LLM-driven extraction without pre-written CSS/XPath selectors. However, the evidence doesn't explicitly describe the underlying mechanism as an LLM 'deciding' fields freely versus schema-guided extraction, and there's no example of open-ended field discovery without a supplied schema. Missing for 10: evidence of schema-less/free-form field discovery, and independent hands-on confirmation of extraction quality without selectors.
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
developerPlug in a local or self-hosted LLM as the extraction backend instead of a cloud-only model
weight 2 · round drawnApifynone0/10No evidence that Apify supports plugging in a local or self-hosted LLM as the extraction backend; documentation covers Actors, CLI, MCP server, and marketplace but nothing about swapping in self-hosted/local models for extraction tasks.
Basic scraping
developerScrape a web page with a single API call and get its raw HTML back
weight 3 · round to Context.devApify's Actor marketplace and public REST API (openapi.json) mean a developer could run a scraping Actor and retrieve HTML via one API call, but no evidence item explicitly documents a single-call 'get raw HTML' endpoint or a specific ready-made scraper Actor's output format. Missing for 10: explicit docs/example showing an API call that returns raw HTML, and any hands-on confirmation of extraction quality/fidelity for that use case.
- [claimed-docs] “Marketplace of 64,279 Actors”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
Context.dev's primary scrape endpoints convert pages to Markdown by default (docs-1, docs-2), and raw HTML is only mentioned as an output option for the async batch-crawl job that must be polled for completion (docs-3), not as an immediate single-call response for a single page. This satisfies the general 'scrape a page via API' need but not the specific 'single call → raw HTML' expectation. Missing for 10: documented synchronous single-page endpoint that returns raw HTML directly, independent confirmation of HTML fidelity/quality.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
Data safety
data-engineerAutomatically detect and filter personally identifiable information out of scraped content before it reaches storage
weight 2 · round drawnApifynone0/10No evidence of any built-in PII detection or filtering capability before data reaches storage; docs cover Actor development, CLI, scheduling, monitoring, proxies, and MCP integration but nothing about PII redaction or compliance filtering.
Document extraction
data-engineerExtract text content from PDFs, Word, Excel, and PowerPoint files without hosting them myself
weight 2 · round to Context.devApifynone0/10No evidence pack items mention PDF/Word/Excel/PowerPoint text extraction capability or any document-parsing Actor; the pack only covers general Actor development, CLI, MCP, scraping/web crawling tooling.
Docs explicitly describe a 'parse-documents' API that converts PDFs, Office documents, and spreadsheets into Markdown, including OCR recovery for scanned PDFs, delivered as a hosted API (no self-hosting required). Missing for 10: independent/hands-on verification of extraction quality and no explicit mention of PowerPoint file type beyond generic 'Office documents'.
- [claimed-docs] “Convert PDFs, Office documents, spreadsheets, and other files into Markdown. Recover scanned PDF pages with optional OCR.”
Multimodal extraction
ai-native userGet automatic captions for images on a page so a text-only model can reason about visual content
weight 2 · round drawnApifynone0/10No evidence of any image captioning, alt-text generation, or vision-to-text capability in Apify's docs or community mentions; the evidence pack covers Actors, scraping, CLI, MCP, and proxying but nothing about generating captions for images to aid text-only model reasoning.
Context.devnone0/10No evidence of automatic image captioning or alt-text generation for visual content; the product's extraction focuses on Markdown/JSON/screenshots and document parsing, not describing images for text-only models. Missing for 10: any mention of image captioning, vision-to-text description, or alt-text generation feature.
Search integration
developerSearch the web and get full page content from results in a single call instead of just links and snippets
weight 3 · round drawnApifynone0/10The evidence pack shows only generic Apify platform docs (Actors, CLI, MCP server, marketplace) with no mention of a specific search-plus-full-content extraction capability or actor (e.g., a RAG/web-search actor) that returns full page content alongside search results in one call.
Context.devnone0/10Context.dev's documented capabilities are URL-based (crawl, scrape, extract, sitemap discovery, screenshot, document parsing, monitoring) but no evidence shows a web-search endpoint that returns full page content for search results in one call — 'discover website URLs' only reads a site's own sitemap, not the open web.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Read a website's public sitemaps and return a filtered URL list without rendering each page.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
Selector extraction
developerExtract specific fields from a page using CSS or XPath selector rules
weight 3 · round to ApifyApify's ecosystem integrates with Playwright, Puppeteer, Selenium, Scrapy, and Crawlee (apify-docs-4), all of which support CSS/XPath selector-based extraction, implying the capability exists, but the evidence pack contains no direct documentation of a selector-based extraction feature (e.g., Web Scraper Actor page-function/selector config) or examples showing CSS/XPath rule usage. missing for 10: explicit docs or examples of CSS/XPath selector extraction features, independent confirmation of selector-based scraping workflows.
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
Structured data handling
data-engineerExtract data from very large tables using intelligent chunking so it fits within processing limits
weight 1 · round drawnApifynone0/10No evidence pack items address extracting data from large tables or intelligent chunking to fit processing limits; docs cover Actors, scheduling, proxies, MCP, CLI, but nothing about table-size chunking strategies.
Js rendering — handling JavaScript-heavy pages — rendering, waiting, dynamic contentJs rendering
Handling JavaScript-heavy pages — rendering, waiting, dynamic content
Headless rendering
developerRender JavaScript-heavy single-page applications and get the fully rendered HTML
weight 3 · round drawnApify supports Playwright, Puppeteer, and Crawlee for browser automation, which are standard tools for rendering JS-heavy SPAs and extracting fully rendered HTML, and its Actor marketplace includes ready-made scrapers for this purpose. However, the evidence pack lacks explicit first-party documentation or examples demonstrating headless-browser rendering output or a dedicated 'render HTML' API/endpoint, relying instead on general framework compatibility claims. Missing for 10: explicit docs/tutorial on rendering SPAs and returning full HTML, hands-on/independent verification of rendering fidelity, and a dedicated rendering API example.
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Marketplace of 64,279 Actors”
- [community] “Currently I use phantomjs via selenium hub for a product and would like to migrate to chrome but couldn't [find] much information on how to …”
Context.dev supports browser actions (click/wait/scroll) before scraping, and screenshot rendering, implying JS execution via a real browser, and crawl/scrape guides return Markdown/HTML output — suggesting rendered SPA content is retrievable. However, there is no explicit statement that scraping fully executes JavaScript-heavy SPAs or waits for hydration/network-idle by default, and no independent/hands-on confirmation of SPA rendering fidelity. missing for 10: explicit documentation confirming full JS/SPA rendering (e.g., wait-for-network-idle, headless browser execution) as default behavior, and independent verification of rendered output correctness for JS-heavy sites.
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
- [claimed-docs] “Render an exact URL or a resolved site page and return a viewport, full-page, or offset PNG capture.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
developerHave the API wait for a specific selector to appear before returning the rendered page
weight 2 · round to Context.devApifynone0/10No evidence in the pack mentions waiting for a specific selector before returning rendered page; only generic mentions of Playwright/Puppeteer/Crawlee support are given, without documenting a wait-for-selector API parameter or option.
Docs describe browser actions supporting 'wait' among click/scroll before scraping or extracting a page, which directly matches waiting for content before returning rendered output, but there's no explicit mention of waiting for a CSS/DOM selector specifically (vs. fixed delays) nor independent confirmation of this behavior. missing for 10: explicit selector-based wait documentation, example showing selector syntax, independent/hands-on verification.
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
Interactive automation
developerAccess a managed remote browser sandbox for interactive, manual browsing workflows
weight 2 · round drawnApifynone0/10Apify's evidence covers Actors, SDKs, CLI, MCP server, and browser automation libraries for building automated scraping/crawling workflows, but there is no mention of an interactive, manual remote browser sandbox (like a live browser session a developer can control interactively for manual browsing). This is a distinct capability (e.g., live view/remote debugging is not documented here) rather than automated headless browser execution.
developerKeep interacting with an already-scraped page, clicking and filling forms to reach content behind a login wall
weight 2 · round to ApifyApify supports Playwright/Puppeteer/Selenium/Crawlee for building Actors that could interact with pages (clicking, filling forms, navigating login walls) via browser automation, but the evidence pack contains no direct documentation or example describing session persistence, interactive multi-step navigation through login walls, or maintaining state across scraped pages. Missing for 10: explicit documentation/example of stateful interaction with an already-loaded page (form-fill, click-through, login-wall bypass), session/cookie persistence guidance, and independent confirmation of this workflow.
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Develop your own Actor”
- [claimed-docs] “Software toolkits for developing new Actors.”
Context.dev documents browser actions (click, wait, scroll) that can run before a scrape or extraction, which supports some interactive page manipulation, but there is no evidence of form-filling, typing credentials, or a persistent multi-step session capable of reaching authenticated/login-walled content. Missing for 10: explicit support for filling login forms/typing input, session/cookie persistence across interactions, and any documented login-wall use case or example.
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
developerScript page interactions like clicking, filling inputs, and scrolling before content is returned
weight 3 · round to Context.devApify supports building Actors with Playwright, Puppeteer, Selenium, and Crawlee, which are libraries capable of scripting clicks, filling inputs, and scrolling before content extraction, but the evidence pack only asserts library compatibility rather than showing documented examples or tutorials of interaction scripting within Apify Actors. Missing for 10: dedicated docs/tutorials demonstrating click/fill/scroll interaction patterns within an Actor, and independent hands-on confirmation of this workflow.
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Develop your own Actor”
- [claimed-docs] “Software toolkits for developing new Actors.”
Docs explicitly describe a browser-actions capability allowing click, wait, or scroll before scraping/extracting content, with success verification, directly matching the story. Missing for 10: independent/hands-on corroboration of scripted interactions beyond first-party docs, and no detail on filling form inputs specifically.
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
Render configuration
developerControl the browser viewport width and height when rendering a page
weight 1 · round to Context.devApifynone0/10No evidence pack item mentions viewport width/height control or browser rendering configuration; while Apify supports Playwright/Puppeteer/Crawlee generically, no specific documentation of viewport control is cited. Missing for 10: any docs or examples showing viewport/window size configuration in Apify Actors or SDK.
The screenshot guide mentions a 'viewport' capture mode alongside full-page and offset options, implying some viewport-based rendering, but no evidence specifies developer control over exact width/height dimensions. missing for 10: explicit API parameters for setting viewport width and height, documentation confirming custom viewport sizing, and any hands-on confirmation.
- [claimed-docs] “Render an exact URL or a resolved site page and return a viewport, full-page, or offset PNG capture.”
Session persistence
developerPass my own session cookies so the API fetches pages requiring authentication
weight 2 · round drawnApifynone0/10No evidence pack item mentions passing custom session cookies or authentication headers for fetching pages behind login; docs listed cover general Actor development, CLI, MCP, and marketplace features but nothing about cookie/session injection.
developerReuse a persistent browser profile with saved cookies and login state across multiple requests
weight 2 · round drawnApifynone0/10No evidence in the pack mentions persistent browser profiles, cookie storage, or session/login state reuse across requests; docs only cover general Actor development, CLI, SDKs, proxies, and scheduling.
Context.devnone0/10No evidence of persistent browser profiles, saved cookies, or reusable login/session state across requests; browser-actions doc only covers click/wait/scroll per single request. Missing for 10: any mention of persistent sessions, cookie storage, authentication state reuse, or profile management across multiple API calls.
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
ai-native userDo everything through the API that I can do in the UI
weight 2 · round drawnApify documents a full OpenAPI-based API (apify-probe-2), a CLI to control the platform from terminal/scripts (apify-docs-3, apify-probe-4), and docs explicitly covering scheduling, monitoring, sharing, proxy, and Actor management—core UI functions all exposed programmatically. This is corroborated by an official MCP server and llms.txt for AI-native access (apify-probe-3, apify-probe-1). Missing for 10: independent/hands-on confirmation that every single UI feature (e.g., billing, org permissions) has 1:1 API parity, and no explicit statement of complete UI/API feature parity.
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Share Actors with other people, manage your organizations and permissions.”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.apify.com/llms.txt # Apify Documentation > Apify is the largest marketplace of tools for AI. Thous…”
Context.dev is API-first: the product's core functions (crawl, extract, screenshot, monitor, brand data) are all documented as API endpoints with an OpenAPI spec, and the CLI/MCP/skill installs are just wrappers around that same API, implying no UI-exclusive functionality. missing for 10: explicit confirmation that the web UI itself exposes zero features unavailable via API (e.g., dashboard-only settings) and independent hands-on verification of full parity.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.context.dev/install-cli”
ai-native userExport all of my data in open formats and leave
weight 3 · round drawnApify provides a CLI and REST/OpenAPI API (apify-docs-3, apify-probe-2, apify-probe-4) that could be used to pull data out of the platform, implying some data portability, but the evidence pack never documents actual dataset export formats (e.g., JSON/CSV/Excel) or an explicit 'export and leave' workflow. missing for 10: explicit documentation of dataset export formats, confirmation of full data portability/deletion, and independent verification that a user can fully migrate data out.
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Context.dev's outputs (Markdown, JSON, HTML) are inherently open, portable formats rather than proprietary lock-in formats, and structured extraction lets users get their scraped/monitored data in JSON Schema-conformant form (docs-1, docs-3, docs-4, docs-9). However there is no explicit account-level 'export all your data and leave' feature (e.g., bulk export of saved crawls, monitors, API key configs, or account deletion with data portability) documented anywhere in the evidence. Missing for 10: dedicated account/data export tooling, documentation of account deletion/data portability guarantees, and independent confirmation that historical crawl/monitor data can be bulk-exported.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
ai-native userRead the product's source under an open license
weight 2 · round drawnApifynone0/10Apify is a proprietary SaaS platform; while its SDKs/CLI and Crawlee library have some open-source components, the evidence pack shows no mention of an open license for the core platform's source code, and the product itself (the Apify platform/service) is closed-source.
ai-native userSelf-host the core product
weight 3 · round drawnApifynone0/10Apify is a cloud SaaS platform; evidence shows Actor development, CLI, MCP server, and marketplace features but no evidence of an open-source self-hostable core platform or on-premise deployment option. The Apify SDK/Crawlee is open source, but the core platform (task scheduling, storage, marketplace) is not shown as self-hostable.
Output formats — stories about output formats in this arenaOutput formats
Stories about output formats in this arena
Content formats
developerReceive scraped content as clean markdown instead of raw HTML
weight 3 · round to Context.devApifynone0/10No evidence in the pack mentions markdown output or content-format conversion capabilities for scraped data; docs references cover Actors, CLI, MCP, scheduling, proxies, etc., but nothing about clean markdown vs raw HTML output.
First-party docs consistently describe scraping/crawling output as Markdown (sync and async crawl endpoints, single-page scrape, document parsing all return Markdown rather than raw HTML), and this is corroborated by a customer case study (SiteGPT) using it to build a knowledge base. Missing for 10: independent hands-on verification of markdown output quality/cleanliness and no explicit sample output shown.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Convert PDFs, Office documents, spreadsheets, and other files into Markdown. Recover scanned PDF pages with optional OCR.”
- [claimed-docs] “SiteGPT, the AI chatbot platform for customer support, switched from Firecrawl to Context.dev to scrape entire websites and turn them into t…”
developerChoose exactly which output format is returned, such as markdown, HTML, text, or frontmatter
weight 2 · round to Context.devApifynone0/10No evidence in the pack shows Apify letting developers select specific output formats like markdown, HTML, text, or frontmatter; the docs cover Actors, CLI, MCP, and platform features but not configurable content-extraction output formats.
Docs show explicit format choice for Markdown (sync/async crawl) and HTML (async crawl), plus JSON output via structured extraction, but no mention of plain 'text' or 'frontmatter' output options anywhere in the docs. missing for 10: explicit text output mode, frontmatter output mode, independent confirmation of format selection working in practice.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
developerReceive scraped content as structured JSON
weight 3 · round to Context.devApifynone0/10The evidence pack contains no documentation or claims about dataset/output formats (e.g., JSON, CSV, Excel) delivered from Actors; only generic docs about building/publishing Actors, CLI, MCP, and API schema are present. Missing for 10: explicit mention of dataset export formats, JSON output examples, or API endpoints returning structured scraped data.
Docs explicitly describe extracting structured JSON matching a user-supplied JSON Schema from crawled pages, with controls for grounding, coverage, and freshness, plus an OpenAPI spec confirming API-driven JSON responses and a CLI that returns JSON for scripting/CI. missing for 10: independent hands-on verification of JSON extraction accuracy/quality beyond vendor docs.
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [probe] “PROBE openapi: HTTP 200 at https://docs.context.dev/openapi.json — contains "openapi" key”
- [claimed-docs] “Call Context.dev from your terminal and use JSON responses in scripts or CI.”
Llm ready output
ai-native userGet clean LLM-ready text directly instead of dealing with blocking, rendering, and messy HTML myself
weight 3 · round to Context.devApify offers anti-blocking proxy rotation, an MCP server for LLM/agent consumption, and llms.txt documentation support, suggesting some LLM-ready output orientation, but the evidence never explicitly documents a 'clean text/markdown extraction' output mode analogous to dedicated LLM-ready scraping tools. Missing for 10: explicit documentation of automatic HTML-to-clean-text/markdown conversion output format, examples of LLM-ready output from Actors, and independent verification that scraped output is directly consumable without further parsing.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Discover and use Actors with AI agents and LLMs via Apify MCP server.”
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.apify.com/llms.txt # Apify Documentation > Apify is the largest marketplace of tools for AI. Thous…”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
Context.dev's core offering is scraping/crawling websites directly into clean Markdown (and JSON) for AI agents, handling rendering, browser actions, and document parsing so the user doesn't deal with raw HTML; this is corroborated by docs and a real-world migration story (SiteGPT switching from Firecrawl). missing for 10: independent hands-on benchmark of output cleanliness/quality versus alternatives, and no detail on how well it strips boilerplate/ads beyond doc claims.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Click, wait, or scroll before scraping or extracting a page, then check which interactions succeeded.”
- [claimed-docs] “Convert PDFs, Office documents, spreadsheets, and other files into Markdown. Recover scanned PDF pages with optional OCR.”
- [claimed-docs] “SiteGPT, the AI chatbot platform for customer support, switched from Firecrawl to Context.dev to scrape entire websites and turn them into t…”
ai-native userRequest semantically chunked output instead of one large content blob, so it feeds cleanly into a retrieval pipeline
weight 2 · round drawnApifynone0/10No evidence in the pack indicates Apify offers semantic chunking of output content for retrieval pipelines; docs cover Actor development, CLI, MCP integration, scheduling, and proxy rotation, but nothing about chunked/segmented output formats.
Context.devnone0/10Context.dev's docs describe scraping/crawling into full-page Markdown, JSON extraction, and document parsing, but nowhere mention a chunking feature (e.g., configurable chunk size, semantic segmentation, or overlap controls) intended for retrieval pipelines. Output is delivered as whole-page Markdown/HTML/JSON blobs per page, not sub-page semantic chunks.
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Convert PDFs, Office documents, spreadsheets, and other files into Markdown. Recover scanned PDF pages with optional OCR.”
Visual capture
developerCapture a screenshot of a full page or a specific selected area
weight 2 · round to Context.devApifynone0/10The evidence pack contains no mention of screenshot capture functionality (full-page or selector-based) in any Apify docs, community posts, or probes; while Apify supports Playwright/Puppeteer which could enable screenshots, no direct evidence documents this capability.
Docs explicitly describe rendering an exact URL or resolved page and returning a viewport, full-page, or offset PNG capture, directly matching the story of full-page or selected-area screenshots. Missing for 10: independent/hands-on corroboration of screenshot quality or selector-based area capture beyond viewport/offset options.
- [claimed-docs] “Render an exact URL or a resolved site page and return a viewport, full-page, or offset PNG capture.”
Pricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits
Free-tier ceilings, usage caps, and rate limits before you have to pay
Cost optimization
developerLet the API automatically pick the cheapest configuration that still succeeds
weight 2 · round drawnApifynone0/10No evidence of any automatic cost-optimization or configuration-selection feature; Apify's docs cover Actor development, scheduling, monitoring, proxies, and CLI/API tooling but nothing about automatically choosing the cheapest configuration that still succeeds.
developerBlock ads on the target page to speed up scraping requests
weight 1 · round drawnApifynone0/10Evidence pack shows Apify's proxy/IP rotation, Actor development, CLI, MCP, and marketplace features, but no mention of ad-blocking or resource-blocking capabilities for target pages to speed up scraping.
Context.devnone0/10No evidence pack item mentions ad-blocking, resource blocking, or any performance optimization feature to skip ads/media during scraping; the docs cover crawling, extraction, screenshots, and browser actions but never ad-blocking specifically. Missing for 10: any documentation of an ad-block or resource-blocking option, any performance/speed benefit tied to blocking ads.
developerBlock images and CSS resources by default to reduce bandwidth and speed up requests
weight 1 · round drawnApifynone0/10No evidence pack item mentions blocking images/CSS resources or any bandwidth-saving resource filtering feature; while Apify's underlying crawlers (Puppeteer/Playwright) could support this, no documentation here confirms a default or built-in option for it.
ai-native userSet how much reasoning effort an autonomous agent spends on a data-gathering task (low, medium, high)
weight 2 · round drawnApifynone0/10No evidence Apify exposes a reasoning-effort control (low/medium/high) for agents on data-gathering tasks; the docs cover Actors, CLI, scheduling, proxies, and MCP integration but nothing about configurable reasoning depth or agent 'effort' levels.
Cost transparency
developerWhether exceeding my plan's monthly credit or request quota triggers overage charges or a hard cutoff
weight 3 · round drawnApifynone0/10No evidence in the pack addresses what happens when a plan's monthly credit or request quota is exceeded—no mention of overage billing, pay-as-you-go charges, or hard cutoffs/service suspension. Missing for 10: any pricing/billing docs on overage policy, quota enforcement behavior, or account throttling upon limit breach.
developerWhether failed, blocked, or empty-result requests still consume my billing quota
weight 2 · round to Context.devApifynone0/10No evidence in the pack addresses whether failed, blocked, or empty-result runs still consume billing quota/compute units; none of the docs or community items discuss billing treatment of failed or empty results.
Docs explicitly state that in the timeout/return-partial flow, if no usable result exists the request 'fails without a charge,' directly addressing billing behavior on failure. However, there's no broader documentation covering all failure modes (e.g., blocked requests, empty-result extractions, rate-limited calls) confirming whether they also skip billing. Missing for 10: explicit policy for blocked requests, empty JSON extraction results, and general error responses beyond the timeout optimization guide; independent/community confirmation of billing behavior.
- [claimed-docs] “`return-partial` | Return usable completed work with a completion marker. If no usable result exists, fail without a charge.”
developerSet a spending cap or usage alert so proxy/credit consumption doesn't silently blow past my budget
weight 3 · round drawnApifynone0/10No evidence pack item mentions spending caps, budget limits, or usage alerts for proxy/credit consumption; docs snippets cover Actor development, scheduling, monitoring performance/data quality, but not billing/usage limit controls.
Performance tuning
developerTrade off latency against completeness by controlling exactly when content is returned
weight 1 · round to Context.devApifynone0/10No evidence pack items address configurable latency-vs-completeness tradeoffs (e.g., streaming partial results, timeouts, or synchronous vs async return controls); docs cover scheduling, monitoring, proxies, and Actor development but not this specific control.
Context.dev offers explicit controls that trade off latency vs completeness: synchronous small crawls (fast, limited to 500 pages) vs async background crawls up to 25,000 pages, plus a 'return-partial' timeout policy that returns usable completed work with a completion marker rather than waiting for full completion. This directly supports controlling when content is returned along a latency/completeness axis, though it's documented only in claimed-docs with no independent hands-on validation of the tradeoff behavior. Missing for 10: independent/community confirmation of the return-partial and sync/async tradeoff working as documented, and more granular mid-request streaming or partial-result controls beyond the two crawl modes and timeout policy.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “`return-partial` | Return usable completed work with a completion marker. If no usable result exists, fail without a charge.”
Plan scale limits
data-engineerThe maximum concurrent sessions or requests allowed on my pricing tier and the cost to raise that cap
weight 2 · round drawnApifynone0/10No evidence pack item documents concurrent session/request caps per pricing tier or the cost to increase them; nothing addresses concurrency limits or upgrade pricing.
Context.devnone0/10Docs mention rate-limit headers exist and per-minute limits apply, but there is no evidence of tier-specific concurrency/session caps or the cost to raise them. Missing for 10: documented tier limits table, concrete numeric caps per plan, and pricing/upgrade path to raise the cap.
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
ai-native userChoose where my data is stored (region/residency)
weight 2 · round drawnApifynone0/10No evidence in the pack mentions data residency, region selection, or storage location controls for Apify; this is a fair question for a cloud data platform but is unaddressed.
Context.devnone0/10No evidence anywhere in the pack mentions data residency, region selection, or storage location options for Context.dev; the product is a web-scraping/data API with no documented control over where data is stored. Missing for 10: any mention of regional hosting, data residency options, or compliance certifications tied to storage location.
ai-native userPrevent my data from being used to train AI models
weight 3 · round drawnApifynone0/10No evidence pack items mention AI training data opt-out, data usage policies for model training, or privacy controls addressing this specific concern; all citations relate to Actor development, marketplace, CLI, and MCP features unrelated to data-training privacy.
ai-native userControl data retention and deletion
weight 2 · round drawnApifynone0/10No evidence pack items address data retention policies, dataset/storage expiration controls, or deletion mechanisms for user data on the Apify platform. Missing for 10: documentation on data retention periods, deletion APIs/controls, GDPR-related data handling, or account/data export-and-delete workflows.
ai-native userOpt out of telemetry and usage tracking
weight 2 · round drawnApifynone0/10No evidence pack items mention telemetry, usage tracking, or an opt-out mechanism for Apify's CLI, SDK, or platform; all citations concern unrelated features like Actors, MCP, CLI commands, and marketplace stats.
Scale reliability — behavior under load — scaling limits, uptime, failure handlingScale reliability
Behavior under load — scaling limits, uptime, failure handling
Ai driven crawling
ai-native userRely on adaptive crawling that automatically stops once enough information has been gathered to answer my query
weight 2 · round drawnApifynone0/10No evidence describes adaptive crawling that dynamically stops once sufficient information is gathered to answer a query; Apify's docs cover Actors, scheduling, proxies, MCP integration, and CLI but nothing about query-driven adaptive stopping logic.
Context.devnone0/10The docs describe crawling with fixed page caps (500 for sync, 25,000 for async) and extraction with 'coverage' controls, but there is no evidence of an adaptive mechanism that halts crawling once sufficient information for a query has been gathered.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
Batch processing
data-engineerBatch scrape thousands of URLs asynchronously
weight 3 · round to Context.devApify's platform is built around Actors (scrapers) that run at scale in the cloud, with scheduling, proxy rotation to avoid blocking, monitoring/alerts, and CLI/API control — all consistent with batch-scraping thousands of URLs asynchronously. However, no evidence pack item explicitly documents async batch job queuing, concurrency limits, or dataset-scale benchmarks for 'thousands of URLs' specifically. missing for 10: explicit documentation/benchmarks of large-scale async URL batch scraping, concurrency/queue management details, and independent hands-on validation of scale claims.
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Docs explicitly describe an async background crawl job handling up to 25,000 pages with progress tracking and retrieval on completion, plus rate-limit headers and partial-result timeout handling that support reliability at scale. However, this is framed as crawling one site rather than an arbitrary list of thousands of distinct URLs, and there is no independent/hands-on evidence confirming real-world throughput or reliability at that scale. Missing for 10: evidence of scraping an arbitrary batch/list of thousands of URLs (not just one site's crawl), independent benchmarks or user reports validating async batch reliability at scale.
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “`return-partial` | Return usable completed work with a completion marker. If no usable result exists, fail without a charge.”
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
developerApply different crawl configurations to different URL patterns within a single batch job
weight 1 · round drawnApifynone0/10No evidence in the pack shows per-URL-pattern crawl configuration within a single job; docs mention general Actor development, scheduling, proxy rotation, and CLI/MCP tooling but nothing about applying different crawl rules to different URL patterns in one batch job.
Context.devnone0/10The docs describe a single batch crawl job (up to 25,000 pages) with one set of settings, but there is no evidence of applying different crawl configurations to different URL patterns within the same job.
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
Concurrency
data-engineerSpin up many concurrent scraping sessions to gather data at scale
weight 3 · round to ApifyApify's platform supports running Actors (scrapers) with IP rotation to avoid blocking, scheduling, monitoring, and CLI/API control, which implies infrastructure for scaling scraping jobs, but the evidence pack lacks explicit documentation on concurrency limits, parallel run orchestration, or autoscaling guarantees for many simultaneous sessions. Missing for 10: explicit docs on concurrent run limits/autoscaling, benchmarks or case studies demonstrating large-scale concurrent scraping, and independent verification of scale-reliability under load.
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
Context.dev supports large single crawls (up to 25,000 pages async) and exposes rate-limit headers, implying some capacity for scaled scraping, but there is no explicit documentation of running many concurrent scraping sessions or session-level concurrency controls. Community feedback also raises doubts about scaling to high-volume/high-value scraping due to lack of rotating/residential proxy support. missing for 10: explicit concurrency/session-limit documentation, evidence of parallel job orchestration, and independent benchmarks confirming multi-session scale.
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
- [community] “Seems wildly expensive, furthermore not a single mention of "ip" on homepage? Not using rotating ip's, residential proxies? AKA unusable for…”
- [community] “Are you using residential proxies? How do you handle websites that don't want to be scraped. EG if I start passing in Linkedin pages what is…”
Crawl compliance
data-engineerConfigure the crawler to respect robots.txt rules and target-site rate limits automatically
weight 2 · round drawnApifynone0/10Evidence mentions IP rotation to avoid blocking and general Actor development/scheduling docs, but nothing explicitly addresses automatic robots.txt compliance or configurable rate-limiting to respect target-site limits. missing for 10: robots.txt compliance settings, automatic rate-limit/throttling configuration, documentation or community confirmation of these specific features.
- [claimed-docs] “Avoid blocking by smartly rotating datacenter and residential IP addresses.”
Context.devnone0/10No documentation describes automatic robots.txt compliance or target-site rate-limiting; the only rate-limit doc (context-dev-docs-18) covers API-caller limits, not crawl politeness. Community evidence (context-dev-comm-4) even states the company relies on a manual opt-out blocklist rather than respecting robots.txt automatically, undercutting the story further.
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
- [community] “\"Websites can opt out of our service, and we respect these requests and add them to our block list.\" I.e: robots.txt already exists and is…”
Fault tolerance
data-engineerResume a crashed deep crawl from a saved checkpoint instead of restarting from scratch
weight 2 · round drawnApifynone0/10No evidence in the pack mentions checkpointing or resuming a crashed deep crawl; Apify docs cover Actors, scheduling, monitoring, CLI, MCP, etc., but nothing about saving/restoring crawl state after a crash. This is a plausible axis for a scraping platform, so absence of evidence yields 'none'.
Context.devnone0/10Evidence shows async batch crawling with progress tracking (up to 25,000 pages) but no mention of checkpointing or resuming a crashed crawl from a saved state; only completed-job retrieval or partial-result return on timeout is documented, not crash recovery/resume.
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “`return-partial` | Return usable completed work with a completion marker. If no usable result exists, fail without a charge.”
Operational transparency
data-engineerCheck a public status page showing uptime history and past incident postmortems before committing to the service
weight 2 · round drawnApifynone0/10No evidence of a public status page, uptime history, or incident postmortems anywhere in the pack; only docs, community sentiment, and API/CLI probes are provided.
Scheduling monitoring
data-engineerMonitor target pages for content changes, such as price or listing updates, and get notified as they happen
weight 2 · round to Context.devApify offers scheduling to run Actors periodically (apify-docs-6) and general Actor monitoring/alerting (apify-docs-7), which together could underpin a page-change-monitoring workflow, and its marketplace likely has ready-made 'content checker' Actors, but no evidence pack item explicitly documents a change-detection/diffing feature or notification-on-change capability for target pages like prices or listings. Missing for 10: explicit docs on content-diff/change-detection Actors, notification channels (email/webhook/Slack) triggered specifically by detected content changes, and independent confirmation of this exact use case.
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
Docs explicitly describe a monitoring feature that watches a page, sitemap, or dataset on a schedule and delivers signed change events, directly matching the story's core ask. However, there's no independent/hands-on corroboration of this feature working in practice, and no detail on notification channels (webhooks, email, etc.) or reliability at scale. Missing for 10: independent evidence of monitoring reliability, details on notification delivery mechanisms/channels, and evidence of scale/performance under continuous monitoring.
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
data-engineerMonitor job performance, validate data quality, and receive alerts when something fails
weight 2 · round to ApifyApify docs explicitly state the platform lets users check Actor performance, validate data quality, and receive alerts, directly matching the story. Missing for 10: independent/hands-on corroboration of monitoring/alerting in practice and detail on alert configuration options beyond the single doc line.
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
Context.dev offers async crawl jobs with progress tracking (docs-3), some quality controls like grounding/coverage/freshness for extraction (docs-4), and scheduled change monitoring with signed events (docs-9), which loosely cover job status and alerting. However there is no dedicated job-performance dashboard, no explicit failure-alert/webhook system for scraping jobs, and no formal data-quality validation framework described. Missing for 10: job performance metrics/dashboard, explicit failure alerting (e.g. webhooks on job error), and structured data quality checks beyond extraction fidelity.
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “Crawl relevant pages and return an object that matches your JSON Schema, with controls for grounding, coverage, and freshness.”
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
- [claimed-docs] “`return-partial` | Return usable completed work with a completion marker. If no usable result exists, fail without a charge.”
- [claimed-docs] “Authenticated API responses expose these headers when a per-minute limit applies”
developerMonitor live system metrics and worker/browser pool status through a real-time dashboard
weight 1 · round to ApifyApify docs mention monitoring Actor performance, data quality checks, and alerts (apify-docs-7), implying some run/status visibility, but there's no concrete evidence of a real-time dashboard showing live system metrics or worker/browser pool status specifically. Missing for 10: explicit dashboard UI showing live resource/worker pool metrics, screenshots or docs describing real-time monitoring views, and independent confirmation of dashboard capabilities.
- [claimed-docs] “Check the performance of your Actors, validate data quality, and receive alerts.”
developerSchedule scraping jobs to run automatically at specific times
weight 2 · round to ApifyApify docs explicitly state scheduling functionality: "Automatically start Actors and saved tasks at specific times," directly matching the story of scheduling scraping jobs to run automatically. This is corroborated by CLI/API tooling for platform control, though there's no independent hands-on report specifically validating the scheduler feature. Missing for 10: independent/community confirmation of scheduling reliability, and more detail on schedule configuration options (cron, timezone, etc.).
- [claimed-docs] “Automatically start Actors and saved tasks at specific times.”
- [claimed-docs] “Control the Apify platform from terminal or shell scripts.”
- [probe] “official CLI documented at https://docs.apify.com/cli/”
Context.dev's monitor-website-changes feature watches a page, sitemap, or dataset "on a schedule" and emits change events, which functions as scheduled recurring scraping, but this is framed narrowly as change-detection rather than a general-purpose cron/scheduler for arbitrary scrape/crawl jobs. Missing for 10: explicit documentation of configurable schedule intervals/cron syntax, ability to schedule full crawl or extract jobs (not just change monitors), and any independent/hands-on confirmation of scheduling reliability.
- [claimed-docs] “Watch a page, sitemap, or structured dataset on a schedule and receive signed change events.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
Site crawling
data-engineerRun a deep crawl using a breadth-first strategy with a configurable maximum page limit
weight 2 · round to Context.devApifynone0/10While Apify's Crawlee library and Actors are built for web crawling, none of the evidence mentions a breadth-first crawl strategy or a configurable maximum page limit specifically; the docs pack only lists generic feature blurbs (Actor development, scheduling, monitoring, proxies) without crawl-strategy specifics.
Context.dev documents crawling with configurable maximum page limits (500 for sync, up to 25,000 for async batch crawls), satisfying the page-limit part of the story, but no evidence describes a selectable crawl strategy (e.g., breadth-first vs depth-first) as a configurable parameter. Missing for 10: explicit breadth-first strategy option/documentation, evidence of strategy configurability alongside the page limit.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
developerCrawl an entire website and get content from all its pages with one request
weight 3 · round to Context.devApify's ecosystem includes Crawlee and general Actor infrastructure that could power full-site crawling, and marketplace Actors (like website content crawlers) exist implicitly via the Store, but the evidence pack lacks any direct documentation of a single-request 'crawl entire website' Actor, its configuration, or output format. missing for 10: explicit docs/demo of a whole-site crawler Actor invoked via one API call, details on link-following/depth/queue handling, and independent confirmation of successful full-site crawls.
- [claimed-docs] “Apify works great with both Python and JavaScript, as well as Playwright, Puppeteer, Selenium, Scrapy, and Crawlee - our own web crawling an…”
- [claimed-docs] “Marketplace of 64,279 Actors”
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.apify.com/llms.txt # Apify Documentation > Apify is the largest marketplace of tools for AI. Thous…”
- [probe] “PROBE openapi: HTTP 200 at https://docs.apify.com/api/openapi.json — contains "openapi" key”
Docs describe a one-request crawl endpoint that returns page Markdown for a site (up to 500 pages synchronously) plus an async option for up to 25,000 pages, and a real customer (SiteGPT) is cited using it to scrape entire websites into a knowledge base. Missing for 10: independent hands-on verification of crawl completeness/accuracy at scale and no third-party benchmark of crawl reliability beyond vendor docs and one customer quote.
- [claimed-docs] “Crawl a small website section and return page Markdown in one response, with a maximum of 500 pages.”
- [claimed-docs] “Crawl up to 25,000 pages in a background batch, track progress, and retrieve Markdown or HTML when the job finishes.”
- [claimed-docs] “SiteGPT, the AI chatbot platform for customer support, switched from Firecrawl to Context.dev to scrape entire websites and turn them into t…”
- [claimed-docs] “Scrape websites into Markdown, crawl linked pages, and extract JSON for AI agents and applications.”
developerInstantly discover all URLs on a website without fully crawling it
weight 2 · round to Context.devApifynone0/10No evidence of a sitemap/URL-discovery feature (e.g., a dedicated sitemap crawler or 'discover URLs without full crawl' Actor); evidence only covers general crawling, Actors, CLI, MCP, and proxy features. Absence of evidence for this specific capability yields 'none'.
Context.dev has a dedicated URL discovery endpoint that reads a site's public sitemaps and returns a filtered URL list "without rendering each page," explicitly avoiding a full crawl — directly matching the story. Missing for 10: independent/hands-on corroboration of discovery speed or scale beyond vendor docs.
- [claimed-docs] “Read a website's public sitemaps and return a filtered URL list without rendering each page.”
Not comparable on these axes
ai-native userPlug MCP servers into this product so it can use their tools
weight 3 · not comparableApifynone0/10All MCP evidence (apify-docs-10, apify-probe-3) describes Apify exposing its own Actors via an MCP server so external AI agents can use Apify's tools — i.e., Apify acting as an MCP server provider, not as a client that plugs in third-party MCP servers to use their tools. There is no evidence Apify can consume or integrate external MCP servers itself, so the story as stated (product acting as MCP client) is unsupported.
- [claimed-docs] “Discover and use Actors with AI agents and LLMs via Apify MCP server.”
- [probe] “official MCP server documented at https://docs.apify.com/platform/integrations/mcp”
Context.devn/aContext.dev is a web-scraping/data-extraction API/service that itself exposes an MCP server (context-dev-docs-13, context-dev-probe-3) so that AI clients can call ITS tools — it is not an agentic product that would consume other MCP servers' tools. The 'plug MCP servers in' client-role story is a category error for this kind of product.
- [claimed-docs] “Connect your AI client to Context.dev tools for live web and company data.”
- [probe] “official MCP server documented at https://mcp.context.dev/mcp”
ai-native userVersion, review, and roll back my automations
weight 1 · not comparableApifynone0/10The evidence pack covers Actor development, scheduling, monitoring, and marketplace sharing, but contains no mention of versioning Actor code, review workflows, or rollback to prior automation versions. Axis is applicable to an automation/scraping platform but no supporting evidence is present.