Rank #5 of 5 in Developer Docs Platforms
Install
npm install rdme --save-devShowcase


Try itExperimental
See what an agent can do with ReadMe before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; commands tagged live-capable can re-run against the real endpoint from our edge, right now (▶ run live — the exact same request, live and recorded lines always labeled); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).
$npx -y rdme --versionrecorded session — replayed, not liveVerified integrations
No integration evidence found in our corpus for this product yet — that means none was found, never that it doesn’t integrate.
By theme — the product's score on each story themeBy theme
Agenticness — how well agents can access and operate the productAgenticnessevidence →
How well agents can access and operate the product
Ai docs — stories about ai docs in this arenaAi docsevidence →
Stories about ai docs in this arena
Analytics insights — stories about analytics insights in this arenaAnalytics insightsevidence →
Stories about analytics insights in this arena
Api reference — stories about api reference in this arenaApi referenceevidence →
Stories about api reference in this arena
Authoring editing — stories about authoring editing in this arenaAuthoring editingevidence →
Stories about authoring editing in this arena
Automation depth — how much of the product can run unattendedAutomation depthevidence →
How much of the product can run unattended
Collaboration review — stories about collaboration review in this arenaCollaboration reviewevidence →
Stories about collaboration review in this arena
Customization — bending the product to your needs — settings, theming, extension pointsCustomizationevidence →
Bending the product to your needs — settings, theming, extension points
Docs as code — stories about docs as code in this arenaDocs as codeevidence →
Stories about docs as code in this arena
Openness — open source, data portability, and self-hosting storiesOpennessevidence →
Open source, data portability, and self-hosting stories
Privacy posture — data-handling and privacy storiesPrivacy postureevidence →
Data-handling and privacy stories
Publishing hosting — stories about publishing hosting in this arenaPublishing hostingevidence →
Stories about publishing hosting in this arena
Search discovery — stories about search discovery in this arenaSearch discoveryevidence →
Stories about search discovery in this arena
Versioning localization — stories about versioning localization in this arenaVersioning localizationevidence →
Stories about versioning localization in this arena
Story verdicts — every judged story with its evidenceStory verdicts
Follow the green: where the map greys out is where ReadMe stops today. ✓ full · ~ partial · ! disputed · — none · n/a not applicable.
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
API surface
Drive the product through a documented public API
✓8/10
unlocks → Scoped API keys · Machine-readable spec · Versioning policy · API sandbox
Subscribe to events via webhooks
n/an/a
Build against official SDKs
~3/10
Issue scoped/least-privilege API credentials for an agent
—–
Connect an agent via an official MCP server
✓8/10
Download a machine-readable API spec (OpenAPI or equivalent)
—0/10
Rely on versioned APIs with a documented deprecation policy
—0/10
Test against a sandbox environment without touching production data
—0/10
Explore an interactive API reference with runnable examples
✓8/10
Docs for agents
Point an agent at llms.txt or agent-oriented docs
✓9/10
Agentic features
Delegate tasks to a built-in AI assistant inside the product
~6/10
unlocks → MCP client
Operate the product with natural-language commands
~6/10
Plug MCP servers into this product so it can use their tools
—0/10
Get AI-generated insights and suggestions from my data inside the product
~6/10
Set up automations that run autonomously in the background
~4/10
Ai docs — stories about ai docs in this arenaAi docs
Stories about ai docs in this arena
My published docs site exposes its own MCP server that my users' agents can query for search and page content
✓8/10
Agent output
An embedded AI assistant on my docs site answers reader questions with citations into my content
~6/10
A platform AI agent drafts, updates, and reviews my docs — from a prompt, a PR, or a schedule — and ships its work as change requests
~7/10
Analytics insights — stories about analytics insights in this arenaAnalytics insights
Stories about analytics insights in this arena
Api reference — stories about api reference in this arenaApi reference
Stories about api reference in this arena
Authoring editing — stories about authoring editing in this arenaAuthoring editing
Stories about authoring editing in this arena
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
Collaboration review — stories about collaboration review in this arenaCollaboration review
Stories about collaboration review in this arena
Customization — bending the product to your needs — settings, theming, extension pointsCustomization
Bending the product to your needs — settings, theming, extension points
Docs as code — stories about docs as code in this arenaDocs as code
Stories about docs as code in this arena
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
Publishing hosting — stories about publishing hosting in this arenaPublishing hosting
Stories about publishing hosting in this arena
Search discovery — stories about search discovery in this arenaSearch discovery
Stories about search discovery in this arena
Versioning localization — stories about versioning localization in this arenaVersioning localization
Stories about versioning localization in this arena
Sorted by importance (agentic first) (high → low) · 53/53 stories · click a row’s chevron for the rationale and evidence
Connect an agent via an official MCP server G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 8/10 | Tprobed | |
Drive the product through a documented public API G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 8/10 | Tprobed | |
Delegate tasks to a built-in AI assistant inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | partial | 6/10 | Cclaimed | |
Plug MCP servers into this product so it can use their tools G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | none | 0/10 | ||
Point an agent at llms.txt or agent-oriented docs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 9/10 | Tprobed | |
Explore an interactive API reference with runnable examples G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Xcommunity | |
Get AI-generated insights and suggestions from my data inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 6/10 | Cclaimed | |
Operate the product with natural-language commands G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 6/10 | Cclaimed | |
Run the product headlessly / in CI for automation G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 6/10 | Tprobed | |
Use an official CLI G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 5/10 | Tprobed | |
Set up automations that run autonomously in the background G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 4/10 | Cclaimed | |
Build against official SDKs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 3/10 | Tprobed | |
Download a machine-readable API spec (OpenAPI or equivalent) G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | 0/10 | ||
Rely on versioned APIs with a documented deprecation policy G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | 0/10 | ||
Issue scoped/least-privilege API credentials for an agent G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Subscribe to events via webhooks G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | n/a | untested | none yet | |
Test against a sandbox environment without touching production data G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 1 | none | 0/10 | ||
My API reference pages are generated from an OpenAPI spec and stay in sync when the spec changes C Spec driven | developer | Api reference — stories about api reference in this arenaApi reference | 3 | full | 8/10 | Xcommunity | |
My docs live in my own git repository — branches, pull requests, and merges drive what gets published C Git workflow | developer | Docs as code — stories about docs as code in this arenaDocs as code | 3 | full | 8/10 | Cclaimed | |
My published docs site automatically serves llms.txt (and a full-content variant) so agents can index it C Agent output | ai-native user | Ai docs — stories about ai docs in this arenaAi docs | 3 | full | 8/10 | Tprobed | |
My published docs site exposes its own MCP server that my users' agents can query for search and page content C Agent access | ai-native user | Ai docs — stories about ai docs in this arenaAi docs | 3 | full | 8/10 | Tprobed | |
Every published page serves clean markdown at its URL (e.g. appending .md) so agents skip the HTML C Agent output | ai-native user | Ai docs — stories about ai docs in this arenaAi docs | 3 | full | 7/10 | Tprobed | |
Export all of my data in open formats and leave G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | partial | 5/10 | Cclaimed | |
I author pages in Markdown/MDX with rich components — tabs, callouts, code groups, steps — without writing custom HTML C Authoring | technical writer | Authoring editing — stories about authoring editing in this arenaAuthoring editing | 3 | partial | 5/10 | Cclaimed | |
I publish versioned documentation per product or API version, and readers switch versions from the site C Versioning | developer | Versioning localization — stories about versioning localization in this arenaVersioning localization | 3 | partial | 5/10 | Cclaimed | |
Define rules that trigger actions automatically on events G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 3 | none | 0/10 | ||
Readers get fast, typo-tolerant, relevance-ranked search over the whole docs site out of the box C Search | developer | Search discovery — stories about search discovery in this arenaSearch discovery | 3 | none | 0/10 | ||
Self-host the core product G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | none | 0/10 | ||
Prevent my data from being used to train AI models G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 3 | none | untested | none yet | |
I customize themes, fonts, and layout — down to custom CSS/JS or my own components — so the docs match my brand C Theming | devrel lead | Customization — bending the product to your needs — settings, theming, extension pointsCustomization | 2 | full | 8/10 | Xcommunity | |
I serve docs on my own custom domain or as a /docs subpath of my main site C Domains | devrel lead | Publishing hosting — stories about publishing hosting in this arenaPublishing hosting | 2 | full | 8/10 | Cclaimed | |
Non-technical teammates can edit docs in a visual web editor without touching git, and their changes flow into the same source of truth C Authoring | technical writer | Authoring editing — stories about authoring editing in this arenaAuthoring editing | 2 | full | 8/10 | Cclaimed | |
Readers can try real API calls from an interactive playground embedded in the reference docs C Playground | developer | Api reference — stories about api reference in this arenaApi reference | 2 | full | 8/10 | Xcommunity | |
A platform AI agent drafts, updates, and reviews my docs — from a prompt, a PR, or a schedule — and ships its work as change requests C Writer agent | ai-native user | Ai docs — stories about ai docs in this arenaAi docs | 2 | partial | 7/10 | Cclaimed | |
Automated checks lint my content against a style guide and flag issues before they publish C Quality | technical writer | Authoring editing — stories about authoring editing in this arenaAuthoring editing | 2 | full | 7/10 | Cclaimed | |
An embedded AI assistant on my docs site answers reader questions with citations into my content C Assistant | ai-native user | Ai docs — stories about ai docs in this arenaAi docs | 2 | partial | 6/10 | Cclaimed | |
Do everything through the API that I can do in the UI G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | partial | 6/10 | Tprobed | |
My docs analytics distinguish AI-agent traffic from human traffic so I can see who — or what — is actually reading C Analytics | ai-native user | Analytics insights — stories about analytics insights in this arenaAnalytics insights | 2 | partial | 6/10 | Cclaimed | |
Teammates propose changes that go through review — comments, approvals, and a merge step — before they publish C Review | technical writer | Collaboration review — stories about collaboration review in this arenaCollaboration review | 2 | partial | 6/10 | Cclaimed | |
I see page views, search terms, and reader feedback so I know which docs work and which fail C Analytics | devrel lead | Analytics insights — stories about analytics insights in this arenaAnalytics insights | 2 | partial | 5/10 | Cclaimed | |
Perform bulk operations across many items at once G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | partial | 4/10 | Tprobed | |
Export my entire docs site as a static bundle and host it anywhere, so my content is never locked in C Portability | developer | Publishing hosting — stories about publishing hosting in this arenaPublishing hosting | 2 | partial | 3/10 | Cclaimed | |
CI validation catches broken links and invalid configuration before the site publishes C Quality gates | developer | Docs as code — stories about docs as code in this arenaDocs as code | 2 | none | 0/10 | ||
Control data retention and deletion G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | 0/10 | ||
Choose where my data is stored (region/residency) G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Every docs pull request gets a shareable preview deployment before it merges C Git workflow | developer | Docs as code — stories about docs as code in this arenaDocs as code | 2 | none | untested | none yet | |
Opt out of telemetry and usage tracking G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Read the product's source under an open license G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | none | untested | none yet | |
Schedule recurring jobs or workflows G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | n/a | untested | none yet | |
Reusable snippets and variables keep repeated content in sync across pages C Content reuse | technical writer | Authoring editing — stories about authoring editing in this arenaAuthoring editing | 1 | full | 8/10 | Cclaimed | |
Version, review, and roll back my automations G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 1 | partial | 5/10 | Cclaimed | |
I gate some or all docs behind authentication — password, JWT, or SSO — for customers-only content G Access control | devrel lead | Publishing hosting — stories about publishing hosting in this arenaPublishing hosting | 1 | none | 0/10 | ||
I publish my docs in multiple languages with translated navigation and content C Localization | technical writer | Versioning localization — stories about versioning localization in this arenaVersioning localization | 1 | none | untested | none yet |
Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 36 stories with headroom
What would move ReadMe’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.
Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools
nonemoves agent-readyimpact 45
All MCP-related evidence describes ReadMe publishing its own MCP server so external AI coding assistants (Cursor, Claude Code, VS Code Copilot) can call ReadMe's API/docs tools (readme-docs-3, readme-docs-34, readme-probe-2) — this is the server role, the opposite of what the story asks.
Automation depth — how much of the product can run unattendedDefine rules that trigger actions automatically on events
nonemoves PA Scoreimpact 30
Missing: an event-trigger/automation rules engine, webhook or conditional action framework, evidence of user-defined triggers beyond docs linting/sync.
Search discovery — stories about search discovery in this arenaReaders get fast, typo-tolerant, relevance-ranked search over the whole docs site out of the box
nonemoves PA Scoreimpact 30
The evidence pack describes Ask AI (AI-generated answers from docs) and MCP/agent discoverability features, but contains no mention of a traditional full-text search index, typo-tolerance, or relevance ranking for the docs site itself.
Openness — open source, data portability, and self-hosting storiesSelf-host the core product
nonemoves PA Scoreimpact 30
ReadMe is a SaaS-only hosted documentation platform; there is no evidence of a self-hostable core product, Docker image, or on-prem deployment option.
Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models
nonemoves PA Scoreimpact 30
No evidence in the pack addresses AI training data opt-out or any data-privacy controls related to AI model training; ReadMe's docs cover documentation/AI-assistant features but not this privacy posture.
Agenticness — how well agents can access and operate the productIssue scoped/least-privilege API credentials for an agent
nonemoves agent-readyimpact 30
While ReadMe exposes an MCP server and a general ReadMe API, the evidence pack contains no mention of issuing scoped or least-privilege API credentials specifically for AI agents (e.g., agent-specific API keys, permission scopes, or token restrictions) — only general API key injection for docs personalization and generic API access control.
Agenticness — how well agents can access and operate the productDownload a machine-readable API spec (OpenAPI or equivalent)
nonemoves API qualityimpact 30
Missing: any documented spec-download endpoint, export-as-OpenAPI option, or explicit machine-readable API spec retrieval capability.
Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy
nonemoves API qualityimpact 30
Evidence shows ReadMe offers a 'Versions' feature for customers' own API docs (readme-docs-17, 48, 69) and exposes its own ReadMe API for programmatic control (readme-docs-87), but there is no documentation of a versioning scheme or deprecation policy for ReadMe's own API/product that an AI-native consumer could rely on.
Showing the top 8 of 36 — every none/partial verdict in the story verdicts table is headroom.
Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.
Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map5 surfaces · 34 covered stories
Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.
Main docs33 stories
- Point an agent at llms.txt or agent-oriented docs
- Run the product headlessly / in CI for automation
- Connect an agent via an official MCP server
- Drive the product through a documented public API
- Build against official SDKs
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- Explore an interactive API reference with runnable examples
- My published docs site exposes its own MCP server that my users' agents can query for search and page content
- My published docs site automatically serves llms.txt (and a full-content variant) so agents can index it
- Every published page serves clean markdown at its URL (e.g. appending .md) so agents skip the HTML
- An embedded AI assistant on my docs site answers reader questions with citations into my content
- A platform AI agent drafts, updates, and reviews my docs — from a prompt, a PR, or a schedule — and ships its work as change requests
- My docs analytics distinguish AI-agent traffic from human traffic so I can see who — or what — is actually reading
- I see page views, search terms, and reader feedback so I know which docs work and which fail
- Readers can try real API calls from an interactive playground embedded in the reference docs
- My API reference pages are generated from an OpenAPI spec and stay in sync when the spec changes
- I author pages in Markdown/MDX with rich components — tabs, callouts, code groups, steps — without writing custom HTML
- Non-technical teammates can edit docs in a visual web editor without touching git, and their changes flow into the same source of truth
- Reusable snippets and variables keep repeated content in sync across pages
- Automated checks lint my content against a style guide and flag issues before they publish
- Perform bulk operations across many items at once
- Version, review, and roll back my automations
- Teammates propose changes that go through review — comments, approvals, and a merge step — before they publish
- I customize themes, fonts, and layout — down to custom CSS/JS or my own components — so the docs match my brand
- My docs live in my own git repository — branches, pull requests, and merges drive what gets published
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
- I serve docs on my own custom domain or as a /docs subpath of my main site
- Export my entire docs site as a static bundle and host it anywhere, so my content is never locked in
- I publish versioned documentation per product or API version, and readers switch versions from the site
GitHub README6 stories
llms.txt4 stories
- Point an agent at llms.txt or agent-oriented docs
- Drive the product through a documented public API
- My published docs site automatically serves llms.txt (and a full-content variant) so agents can index it
- Every published page serves clean markdown at its URL (e.g. appending .md) so agents skip the HTML
Hacker News4 stories
- Explore an interactive API reference with runnable examples
- Readers can try real API calls from an interactive playground embedded in the reference docs
- My API reference pages are generated from an OpenAPI spec and stay in sync when the spec changes
- I customize themes, fonts, and layout — down to custom CSS/JS or my own components — so the docs match my brand
Probe proofs — replayable recordings from the probe harnessProbe proofs
Replayable recordings from our probe harness — see the Prove-It protocol to submit one.
$npx -y rdme --versionreproduced$ npx -y rdme --version rdme/10.9.6 darwin-arm64 node-v26.0.0
$curl -s -X POST https://docs.readme.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # the per-project MCP server ReadMe ships, on its own docsreproduced$ curl -s -X POST https://docs.readme.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # the per-project MCP server ReadMe ships, on its own docs
event: message
data: {"result":{"protocolVersion":"2025-06-18","capabilities":{"tools":{"listChanged":false}},"serverInfo":{"name":"ReadMe Documentation","version":"1.0.0"}},"jsonrpc":"2.0","id":1}
$curl -sL 'https://docs.readme.com/llms.txt?query=mcp+server' | head -12 # llms.txt with built-in search, on ReadMe's own docsreproduced$ curl -sL 'https://docs.readme.com/llms.txt?query=mcp+server' | head -12 # llms.txt with built-in search, on ReadMe's own docs # ReadMe Documentation Documentation > Beautiful documentation made easy. Append .md to any documentation page URL to get its markdown version. Pages matching `mcp server`, most relevant first. Fetch https://docs.readme.com/llms.txt for the complete index. ## Search Results - [ReadMe's MCP Server](https://docs.readme.com/main/docs/readmes-mcp-server.md) (ReadMe · Guides): Search, read, and update your documentation from any AI coding assistant or CI pipeline. - [MCP Metrics](https://docs.readme.com/main/docs/mcp-metrics.md) (ReadMe · Guides): See which tools AI agents call on your MCP server, how fast those calls return, and what they asked for. - [MCP](https://docs.readme.com/main/docs/your-projects-mcp-server.md) (ReadMe · Guides): Give your users' AI tools live access to your API spec and docs.
$curl -sL https://docs.readme.com/main/docs/your-projects-mcp-server.md | head -12reproduced$ curl -sL https://docs.readme.com/main/docs/your-projects-mcp-server.md | head -12 --- updatedAt: 2026-08-21T03:05:09.000Z --- Fetch the complete documentation index at: https://docs.readme.com/main/llms.txt. Use this file to discover all available pages before exploring further. Append .md to any documentation page URL to get its markdown version. If a page title in the index already matches your question, fetch that page directly. When no title matches, or finding one means reading a long index, attach a query parameter in the root llms.txt URL like https://docs.readme.com/main/llms.txt?query=<search-query> using 2-4 specific [redacted]words to get only the matching pages, most relevant first. # MCP Give your users' AI tools live access to your API spec and docs.
Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence
5 of 16 testable claims verified · 0 contradicted → integrity 31/100
19 distinct capability claims found in ReadMe’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.
5
Verified
11
Unverified
0
Contradicted
18
Undersold
Verified (5)
“Interactive API reference lets developers make real test calls and see live responses without writing code”
Explore an interactive API reference with runnable examplesfullproof ↗
“Interactive API reference lets developers make real test calls and see live responses without writing code”
Readers can try real API calls from an interactive playground embedded in the reference docsfullproof ↗
“An MCP server gives AI coding assistants (Cursor, Claude Code, VS Code Copilot) a live connection to the API spec and docs”
“Docs appearance can be customized via CSS variables or custom CSS rules”
I customize themes, fonts, and layout — down to custom CSS/JS or my own components — so the docs match my brandfullproof ↗
“An OpenAPI spec can be imported by URL, file upload, or drag-and-drop and transformed into interactive documentation”
My API reference pages are generated from an OpenAPI spec and stay in sync when the spec changesfullproof ↗
Unverified (13)
“Ask AI answers reader questions instantly from the published documentation inside the hub”
An embedded AI assistant on my docs site answers reader questions with citations into my contentpartialproof ↗
“Readers can suggest edits or flag typos/feedback directly via GitHub”
Teammates propose changes that go through review — comments, approvals, and a merge step — before they publishpartialproof ↗
“Custom linter rules can be written in natural language and applied to check every page”
Automated checks lint my content against a style guide and flag issues before they publishfullproof ↗
“Docs Audit runs all linter rules across every page in one pass to surface outdated content, broken links, and style issues”
Automated checks lint my content against a style guide and flag issues before they publishfullproof ↗
“A GitHub AI Writer watches pull requests and proposes doc updates when code changes affect the docs”
A platform AI agent drafts, updates, and reviews my docs — from a prompt, a PR, or a schedule — and ships its work as change requestspartialproof ↗
“MCP Analytics tracks every tool call to the MCP server, showing volume, latency, failures, and which endpoint/query was invoked”
My docs analytics distinguish AI-agent traffic from human traffic so I can see who — or what — is actually readingpartialproof ↗
“Docs content can be written locally or in ReadMe and synced two-way with a connected GitHub/GitLab repository”
My docs live in my own git repository — branches, pull requests, and merges drive what gets publishedfullproof ↗
“Reviews let teammates check changes with an AI Linter or get approval before publishing”
Teammates propose changes that go through review — comments, approvals, and a merge step — before they publishpartialproof ↗
“Docs (or a PDF) can be exported directly from the Branch menu”
Export my entire docs site as a static bundle and host it anywhere, so my content is never locked inpartialproof ↗
“Reusable content blocks can be edited once and the update propagates automatically to every page that uses them”
Reusable snippets and variables keep repeated content in sync across pagesfullproof ↗
“Multiple versions of documentation can be maintained for different product/API versions”
I publish versioned documentation per product or API version, and readers switch versions from the sitepartialproof ↗
“A built-in AI Agent creates, edits, and enhances content across Guides, API References, and Custom Pages via natural-language prompts”
Delegate tasks to a built-in AI assistant inside the productpartialproof ↗
“Docs can be hosted on a custom company domain via project configuration”
I serve docs on my own custom domain or as a /docs subpath of my main sitefullproof ↗
Undersold (18)
Point an agent at llms.txt or agent-oriented docsfullproof ↗
Run the product headlessly / in CI for automationpartialproof ↗
Drive the product through a documented public APIfullproof ↗
Get AI-generated insights and suggestions from my data inside the productpartialproof ↗
Set up automations that run autonomously in the backgroundpartialproof ↗
Operate the product with natural-language commandspartialproof ↗
My published docs site exposes its own MCP server that my users' agents can query for search and page contentfullproof ↗
My published docs site automatically serves llms.txt (and a full-content variant) so agents can index itfullproof ↗
Every published page serves clean markdown at its URL (e.g. appending .md) so agents skip the HTMLfullproof ↗
I see page views, search terms, and reader feedback so I know which docs work and which failpartialproof ↗
I author pages in Markdown/MDX with rich components — tabs, callouts, code groups, steps — without writing custom HTMLpartialproof ↗
Non-technical teammates can edit docs in a visual web editor without touching git, and their changes flow into the same source of truthfullproof ↗
Perform bulk operations across many items at oncepartialproof ↗
Do everything through the API that I can do in the UIpartialproof ↗
Export all of my data in open formats and leavepartialproof ↗
Claims outside our story set (2)
Real capability claims found in ReadMe’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.
“ReadMe crawls a sample of published pages and scores the project against an Agent-Friendly Docs spec”
source ↗“API Metrics report call volume, endpoint usage, and errors for insight into API usage”
source ↗
Business model
Starter plan is free; Pro is $250/month per project with AI features (Ask AI is a $150/month add-on); Enterprise is custom with annual billing.
pricing ↗Score trend
How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.
Try Experimental
Run it in the microterminal →Recorded agent sessions — and a live MCP handshake where the vendor ships one.
Flag
⚑ Flag a verdictThink a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.
For agents
Agent surface uptime MCP up · llms.txt up (tracking since Sep 10 '26)
