Lago vs RevenueCat
open-source · hosted-paid · enterprise-custom
·free-tier · usage-based · enterprise-custom
Lago wins · 27–6 (17 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 to LagoLago has a confirmed live llms.txt at the root domain (HTTP 200) plus a docs-specific llms.txt index and .md-formatted doc pages, explicitly designed for agent consumption, alongside an OpenAPI schema and MCP server for programmatic access. This directly satisfies pointing an agent at agent-oriented docs, with only independent third-party confirmation of agent usage missing for a perfect score. Missing for 10: independent/hands-on verification that an agent successfully consumes these files end-to-end.
- [probe] “PROBE llms.txt: HTTP 200 at https://getlago.com/llms.txt # Lago > Lago is the open-source billing platform for usage-based, subscription-ba…”
- [probe] “PROBE docs-md: HTTP 200 at https://getlago.com/docs/api-reference/intro.md > ## Documentation Index > Fetch the complete documentation index…”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
RevenueCat serves a live llms.txt (HTTP 200) describing itself in agent-friendly terms, and docs pages throughout the evidence pack use the .md suffix convention (agent-oriented docs format) confirming machine-readable documentation exists. missing for 10: no root docs.md index (404) and no OpenAPI spec discoverable, which would round out full agentic documentation coverage.
- [probe] “PROBE llms.txt: HTTP 200 at https://www.revenuecat.com/llms.txt # RevenueCat > RevenueCat is the App Monetization OS for mobile and web app…”
- [probe] “PROBE docs-md: HTTP 404 at https://www.revenuecat.com/docs.md”
- [probe] “PROBE openapi: all candidate paths 404 (https://www.revenuecat.com/openapi.json, https://www.revenuecat.com/swagger.json, https://www.revenu…”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
ai-native userRun the product headlessly / in CI for automation
weight 2 · round to LagoLago is self-hostable via Docker (docs-11), fully API/CLI-driven with a generated command for every endpoint (docs-1) and an OpenAPI 3.1 schema for scripting/client generation (docs-16), and the GitHub repo contains a script that spins up a disposable local Lago instance and runs automated pricing scenarios (gh-1), all consistent with headless/CI automation. However there is no explicit CI/headless-mode documentation, example CI pipeline config, or independent report of running Lago fully headless in a pipeline. Missing for 10: dedicated CI/headless-mode docs, a documented CI pipeline example, and independent confirmation of headless automated runs.
- [claimed-docs] “Docker is the easiest way to get started with the self-hosted version of Lago.”
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [github] “It starts the Lago version that matches this checkout, creates a disposable local organization, and prices three illustrative AI requests.”
RevenueCat exposes a REST API authenticated via API keys and supports server-side data import/export (revenuecat-docs-5, revenuecat-docs-4, revenuecat-docs-7), which enables non-interactive, programmatic use suitable for automation pipelines. However, there is no explicit documentation of CI/CD integration, headless test runners, or scripted deployment workflows. Missing for 10: explicit CI/CD examples, headless SDK testing guidance, and confirmation of non-interactive automation use cases.
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “Importing existing purchase data to RevenueCat can be done server-side, or client-side.”
- [claimed-docs] “RevenueCat delivers your apps' data to a cloud storage provider or to email on a schedule you control.”
ai-native userConnect an agent via an official MCP server
weight 3 · round drawnLago is not itself an AI agent but a billing platform, so publishing an official MCP server is a fair axis; docs explicitly confirm a dedicated MCP server giving AI assistants like Claude direct access to Lago's billing data, plus a probe confirming the page exists. Missing for 10: independent/hands-on third-party verification of the MCP server working in practice.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat documents an official MCP server that lets AI assistants manage subscription apps, Products, Entitlements, etc. directly, without the dashboard, which directly satisfies the story. Missing for 10: independent/hands-on third-party corroboration of the MCP server working, and technical setup/auth details beyond the docs summary.
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
ai-native userUse an official CLI
weight 2 · round to LagoDocs mention that 'every endpoint in this reference has a generated command,' implying an official CLI exists, but there is no dedicated CLI documentation, install instructions, or AI-native framing (e.g., LLM-friendly usage, agent integration) beyond this single line. Missing for 10: explicit CLI install/setup docs, AI-native use-case description, independent confirmation of CLI usage.
- [claimed-docs] “Every endpoint in this reference has a generated command.”
RevenueCatnone0/10No evidence pack item describes a dedicated official CLI tool; the closest items are an MCP server (revenuecat-docs-9), an AI toolkit doc (revenuecat-docs-8), and a natural-language analytics assistant 'Rico' (revenuecat-docs-10), none of which are described as a command-line interface. Missing for 10: explicit CLI product/documentation, installation instructions, command reference, or community confirmation of CLI usage.
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
ai-native userDrive the product through a documented public API
weight 3 · round to LagoLago publishes a full public API reference with generated commands per endpoint, an OpenAPI 3.1 schema (verified live at /openapi.json), explicit versioning/stability guarantees, and docs/llms.txt aimed at AI-native consumption; it even documents an MCP server exposing billing data to AI agents. This is strong first-party and probe-verified evidence of a documented, machine-consumable public API. Missing for 10: independent third-party developer testimonials specifically about API usage/integration experience (community evidence is mostly about billing product value, not API DX).
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “Clients should tolerate additive changes within v1, including new response fields, enum values, endpoints, optional request fields, and webh…”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE llms.txt: HTTP 200 at https://getlago.com/llms.txt # Lago > Lago is the open-source billing platform for usage-based, subscription-ba…”
- [probe] “PROBE docs-md: HTTP 200 at https://getlago.com/docs/api-reference/intro.md > ## Documentation Index > Fetch the complete documentation index…”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat confirms a REST API secured by API keys (revenuecat-docs-5) and even offers an MCP server letting AI assistants manage subscriptions programmatically (revenuecat-docs-9) and an AI toolkit (revenuecat-docs-8), showing real support for AI-driven API access. However, probes for a public OpenAPI/swagger spec or docs.md all 404 (revenuecat-probe-2, revenuecat-probe-3), so a fully documented, discoverable public API reference isn't evidenced. Missing for 10: a published OpenAPI/API reference spec, broader REST endpoint documentation beyond auth, and independent confirmation of programmatic API usage outside RevenueCat's own docs.
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
- [probe] “PROBE docs-md: HTTP 404 at https://www.revenuecat.com/docs.md”
- [probe] “PROBE openapi: all candidate paths 404 (https://www.revenuecat.com/openapi.json, https://www.revenuecat.com/swagger.json, https://www.revenu…”
ai-native userIssue scoped/least-privilege API credentials for an agent
weight 2 · round drawnLagonone0/10Lago's docs describe an MCP server and API access for AI agents but provide no evidence of scoped or least-privilege API key/credential issuance (e.g., role-based keys, permission scopes) for agents; existing docs only mention general API keys and OpenAPI schema access without granular scoping controls.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCatnone0/10Evidence shows RevenueCat uses API keys for authentication (revenuecat-docs-5) and has an MCP server/AI toolkit for agents (revenuecat-docs-8, revenuecat-docs-9), but nothing describes scoped, granular, or least-privilege API key permissions for agents — no mention of read-only keys, role-based scopes, or key restriction settings.
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
ai-native userBuild against official SDKs
weight 2 · round to RevenueCatLago publishes an OpenAPI 3.1 spec and API reference with per-endpoint generated commands, explicitly positioned for generating clients or exposing actions to AI agents, but the evidence never names concrete official first-party SDKs (e.g., language libraries) beyond spec-generated clients. missing for 10: named official SDK packages/libraries, independent developer confirmation of SDK usage, versioning/maintenance details for SDKs.
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
- [claimed-docs] “Clients should tolerate additive changes within v1, including new response fields, enum values, endpoints, optional request fields, and webh…”
RevenueCat ships official native SDKs (iOS, and implied Android/cross-platform per GitHub repo) with well-documented capabilities—purchases, entitlements, customer info, authentication—that developers, including AI-native ones, can build against directly, and this is corroborated by both first-party GitHub repos and extensive docs. Missing for 10: independent hands-on developer corroboration specifically praising SDK integration ergonomics, and explicit multi-platform SDK breadth beyond iOS in the evidence pack.
- [github] “Fetch products, make purchases, and check subscription status with our native SDKs.”
- [claimed-docs] “Entitlements are used to ensure a user has appropriate access to content based on their purchases, without having to manage all of the produ…”
- [claimed-docs] “The CustomerInfo object contains all of the purchase and subscription data available about a customer.”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
ai-native userSubscribe to events via webhooks
weight 2 · round drawnLago documents a webhook system with HMAC signing options (lago-docs-7) and explicit API versioning guarantees for webhook event types (lago-docs-8), meaning any consumer—including an AI agent—can subscribe to billing events via webhooks. missing for 10: a full catalog/list of supported webhook event types, and independent/hands-on confirmation of webhook reliability in production use.
- [claimed-docs] “The second is `HMAC`, which features a shorter payload header and no size restrictions.”
- [claimed-docs] “Clients should tolerate additive changes within v1, including new response fields, enum values, endpoints, optional request fields, and webh…”
RevenueCat explicitly documents webhooks for real-time event notifications, letting external systems (including AI agents) subscribe to subscription/purchase events. Missing for 10: no first-party docs on webhook payload schema/customization or independent hands-on confirmation of reliability, and no mention of AI-specific webhook consumption patterns.
- [github] “Get notified of real-time events through webhooks.”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
Agentic features
ai-native userGet AI-generated insights and suggestions from my data inside the product
weight 2 · round to RevenueCatLago documents specific AI-agent features—an MCP server that gives assistants like Claude direct access to billing data, and a 'Dunning Agent' that reads 12 months of invoices/payments/disputes to inform actions—showing some in-product AI analysis of data. However, this is narrow (payment collection) rather than a general AI-insights/suggestions layer across revenue analytics, plans, or usage data. missing for 10: evidence of AI-generated insights/suggestions surfaced in the main product UI (e.g., revenue analytics, plan optimization), independent/hands-on confirmation the Dunning Agent's outputs are used, and broader scope beyond dunning/collections.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat's Rico feature explicitly lets users ask plain-language questions about their data (e.g. "Why did MRR drop in Germany last week?") and get AI-driven insights, directly matching the story; charts/metrics dashboard provides the underlying data surface. Missing for 10: independent/hands-on validation of Rico's insight quality and broader coverage beyond the single documented example.
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
- [claimed-docs] “RevenueCat charts allow you to understand your user base with key subscription specific metrics, filters, and segments.”
ai-native userSet up automations that run autonomously in the background
weight 2 · round to LagoLago documents a Dunning Agent that autonomously reads account/invoice/payment history and presumably acts on overdue accounts, plus an MCP server exposing billing data to AI agents like Claude, showing some autonomous background automation capability. However, evidence doesn't show a general-purpose automation/agent-builder framework, scheduling, or independent confirmation of the Dunning Agent running unattended in production. missing for 10: broader autonomous automation framework beyond dunning agent, independent/hands-on verification of autonomous background operation, details on triggering/scheduling/monitoring these agents.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat offers webhooks for real-time event notifications and scheduled data exports that run on a set cadence, which are background automations, but these are infrastructure features rather than AI-driven autonomous agentic workflows. The MCP server and AI toolkit let AI assistants configure or query RevenueCat interactively, not run persistent background automations. Missing for 10: evidence of AI agents autonomously triggering actions or workflows in the background without human initiation, scheduling/orchestration of agentic tasks, or any first-party 'automation builder' feature.
- [github] “Get notified of real-time events through webhooks.”
- [claimed-docs] “RevenueCat delivers your apps' data to a cloud storage provider or to email on a schedule you control.”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
ai-native userDelegate tasks to a built-in AI assistant inside the product
weight 3 · round drawnLago ships an 'AI agents' documentation section describing a built-in Dunning Agent that autonomously reads invoices, disputes, and payment provider status to act on overdue accounts, and an MCP server that gives external AI assistants (e.g., Claude) direct access to billing data. This shows some built-in agentic delegation for a specific task (dunning/collections), but there's no evidence of a general-purpose in-product AI assistant users can converse with or delegate arbitrary tasks to. missing for 10: evidence of a general conversational assistant UI, breadth of tasks beyond dunning, independent/hands-on confirmation of the Dunning Agent actually operating in production.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat documents "Rico", a built-in AI assistant in the dashboard that lets users ask plain-language questions about their data instead of digging through charts (revenuecat-docs-10). This shows a built-in assistant capability, but evidence only covers Q&A/insight generation, not broader task delegation or action-taking within the product, and there's no independent/community corroboration of its real-world reliability. Missing for 10: evidence of Rico performing actions/tasks beyond answering questions, and independent user reports validating its usefulness.
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
ai-native userOperate the product with natural-language commands
weight 2 · round drawnLago documents an official MCP server that gives AI assistants like Claude direct access to billing data, plus specialized AI agents (e.g., Dunning Agent) that read account data and OpenAPI schema exposure for AI agents to invoke billing actions — enabling natural-language operation via connected AI assistants. However, this is mediated through external assistants/MCP rather than a built-in NL command interface, and there's no independent/hands-on evidence of actual NL command execution or the breadth of supported commands. Missing for 10: hands-on/independent verification of NL command execution, a native in-product chat/command interface, and documentation of the full range of commands executable via natural language.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat offers an MCP server letting AI assistants manage products/entitlements via natural language, and Rico allows plain-language analytics queries — both first-party docs confirm agentic/NL control of the dashboard. However, this covers admin/analytics operations, not the core end-user subscription flows, and there's no independent/hands-on corroboration of these NL features working reliably. Missing for 10: third-party validation of MCP/Rico usage, broader coverage of NL control across all product surfaces (not just admin tasks).
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
Api quality
ai-native userExplore an interactive API reference with runnable examples
weight 2 · round to LagoDocs confirm a generated command for every endpoint and an OpenAPI 3.1 schema (lago-docs-1, lago-docs-16, lago-probe-3), suggesting a structured, code-snippet-rich API reference, but there is no evidence of an in-browser 'try it out' or runnable execution feature. Missing for 10: explicit interactive 'run this request' UI, hands-on confirmation of executability, and independent corroboration of the reference's interactivity.
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
- [probe] “PROBE docs-md: HTTP 200 at https://getlago.com/docs/api-reference/intro.md > ## Documentation Index > Fetch the complete documentation index…”
RevenueCatnone0/10No evidence of an interactive API reference or runnable examples; probes for openapi/swagger specs and docs.md return 404, and no documentation item describes a try-it-out console or embedded runnable code samples.
ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)
weight 2 · round to LagoLago publishes an OpenAPI 3.1 schema (openapi.json returns 200 with an 'openapi' key) and docs explicitly state it can be used to generate clients, inspect typed operations, or expose actions to an AI agent. missing for 10: no independent third-party corroboration of the spec's completeness or usage beyond vendor docs/probe.
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
RevenueCatnone0/10RevenueCat exposes a REST API (per revenuecat-docs-5) but no evidence of a downloadable OpenAPI/Swagger spec; the probe explicitly found all standard OpenAPI spec paths return 404, and no docs reference a machine-readable API spec.
- [probe] “PROBE openapi: all candidate paths 404 (https://www.revenuecat.com/openapi.json, https://www.revenuecat.com/swagger.json, https://www.revenu…”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
ai-native userTest against a sandbox environment without touching production data
weight 1 · round to LagoLago's self-hosted Docker setup and the GitHub quick-start script that spins up a 'disposable local organization' for testing suggest a way to try Lago without touching production data, but there is no documented dedicated sandbox/test-mode with separate test API keys as many billing platforms provide. Missing for 10: explicit sandbox/test-mode documentation, test vs. live API key separation, and hands-on confirmation that test data is fully isolated from production billing.
- [github] “It starts the Lago version that matches this checkout, creates a disposable local organization, and prices three illustrative AI requests.”
- [claimed-docs] “Docker is the easiest way to get started with the self-hosted version of Lago.”
ai-native userRely on versioned APIs with a documented deprecation policy
weight 2 · round to LagoLago documents an explicit API versioning policy (v1) specifying that clients should tolerate additive changes like new fields, enums, endpoints, and webhook event types, indicating a stable versioned API contract with deprecation-safe evolution rules, and backs this with a published OpenAPI 3.1 schema. Missing for 10: an explicit deprecation/sunset timeline policy (e.g., how long old versions are supported) and independent/community confirmation of version stability in practice.
- [claimed-docs] “Clients should tolerate additive changes within v1, including new response fields, enum values, endpoints, optional request fields, and webh…”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
RevenueCatnone0/10No evidence of API versioning scheme or a documented deprecation policy; OpenAPI spec probes returned 404s and no docs mention version lifecycle or deprecation commitments.
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 drawnLagonone0/10No evidence describes bulk/batch endpoints or batch operations (e.g., bulk invoice creation, bulk customer updates) in Lago's API or UI; documentation only mentions per-endpoint commands and general API access. Missing for 10: any mention of batch/bulk API endpoints, batch job status, or UI batch-select actions.
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
RevenueCatnone0/10The evidence shows RevenueCat's MCP server and AI toolkit let an AI assistant manage individual Products, Entitlements, and Offerings, and server-side import of existing purchase data exists, but nothing describes batch/bulk operations across many items at once (e.g., bulk-editing many products, mass customer updates, or batch API calls) for an AI-native workflow. Missing for full credit: explicit bulk/batch API endpoints, documentation of bulk operations via MCP/AI toolkit, and any example of operating on many items simultaneously.
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
- [claimed-docs] “Importing existing purchase data to RevenueCat can be done server-side, or client-side.”
ai-native userDefine rules that trigger actions automatically on events
weight 3 · round to LagoLago documents webhooks that fire on billing events (lago-docs-7) and a dedicated 'Dunning Agent' that reads account state (invoices, payments, disputes) and presumably acts on overdue-payment events (lago-docs-10), which together resemble event-triggered automation. However, there is no documented general-purpose rule/condition engine letting users define arbitrary 'if event X then action Y' logic beyond these specific built-in agents/webhooks. Missing for 10: a configurable rules/conditions UI or API for arbitrary triggers, and evidence of multiple event types beyond dunning/webhooks.
- [claimed-docs] “The second is `HMAC`, which features a shorter payload header and no size restrictions.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
RevenueCat offers webhooks for real-time event notifications (revenuecat-gh-3) that can be wired to trigger external actions, but there's no built-in rule engine to define conditional logic or automated actions natively within RevenueCat itself. A community feature request explicitly asks for 'timed hooks' like trial-expiry reminders, indicating this kind of automation isn't natively supported (revenuecat-comm-6). Missing for 10: native rule/trigger builder, conditional logic definitions, in-product automated actions beyond raw webhook delivery.
- [github] “Get notified of real-time events through webhooks.”
- [community] “Feature request: handling timed hooks to send notifications, e.g. reminding users before a trial expires and subscription cancels.”
ai-native userSchedule recurring jobs or workflows
weight 2 · round drawnLago's core billing engine inherently runs recurring cycles (monthly/yearly subscription billing) and the Dunning Agent appears to run periodic checks over invoices/payments, which is a recurring automated workflow, but there is no documented feature letting an AI-native user define or schedule arbitrary recurring jobs/workflows via API or agent. missing for 10: explicit job/workflow scheduler, cron-like API, user-configurable recurrence for AI agent tasks beyond built-in billing cycles.
- [claimed-docs] “Yearly: subscription fees are billed on a yearly basis and charges can be billed monthly or annually.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
RevenueCat supports scheduled recurring data exports to cloud storage/email, which is a narrow instance of a recurring job, but there is no evidence of a general-purpose scheduler for recurring workflows or automations (e.g., via MCP/AI toolkit) that an AI-native user could configure. missing for 10: evidence of configurable recurring workflow/job scheduling beyond data exports, integration of scheduling with the MCP/AI toolkit or Rico assistant, and any cron-like automation API.
- [claimed-docs] “RevenueCat delivers your apps' data to a cloud storage provider or to email on a schedule you control.”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
Billing agent access — stories about billing agent access in this arenaBilling agent access
Stories about billing agent access in this arena
Agent operations
ai-native userAn agent can operate my billing — create a subscription, apply a credit, change a plan — through a programmatic surface with scoped permissions
weight 3 · round to LagoLago exposes a full REST API (every endpoint has a generated command) plus an OpenAPI 3.1 schema explicitly positioned for exposing billing actions to AI agents, and ships a documented MCP server giving AI assistants direct access to billing data, with a working example (Dunning Agent) reading account/invoice data. Subscription assignment and plan upgrade/downgrade are documented API-driven flows, supporting the 'create a subscription, change a plan' part of the story. Missing for 10: no explicit documentation of scoped/permissioned API keys or credit-application endpoints for agents, and no independent hands-on report of an agent actually performing these billing operations end-to-end.
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “Customers have the flexibility to easily upgrade or downgrade their plan at any given moment.”
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCat ships an MCP server explicitly for AI assistants to manage subscription apps, Products, Entitlements, and Offerings (revenuecat-docs-9), backed by a REST API authenticated via scoped API keys (revenuecat-docs-5), and SDK/dashboard features let you grant promotional subscriptions and view customer transaction histories (revenuecat-gh-4). However, the evidence centers on catalog/config management (products, entitlements, offerings) rather than explicit end-user billing actions like 'create a subscription', 'apply a credit', or 'change a plan' for a specific customer, and there's no documentation of granular per-action permission scoping beyond generic API keys. Missing for 10: explicit agent-driven customer-level actions (create subscription, apply credit, change plan) and detailed scoped-permission/role model for agent access.
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [github] “See customer transaction histories, chart lifetime value, and grant promotional subscriptions.”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
Agent queries
ai-native userAn agent can answer questions about my billing state — MRR, delinquent accounts, upcoming renewals, a customer's invoices — by querying the platform directly
weight 2 · round to LagoLago ships an official MCP server explicitly described as giving AI assistants 'direct access to Lago's billing data' (lago-docs-9, lago-probe-4), plus a documented OpenAPI schema explicitly positioned for 'exposing billing actions to an AI agent' (lago-docs-16), and a Dunning Agent example that reads a customer's invoices, payments and disputes (lago-docs-10) — directly matching the story of an agent querying billing state like delinquency and invoices. Missing for 10: explicit worked examples/queries for MRR aggregation and upcoming-renewal lookups via the MCP server, and independent (non-vendor) confirmation that these agent queries work in practice.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
RevenueCat's Rico assistant explicitly lets users ask plain-language billing questions like 'why did MRR drop,' and the MCP server/CustomerInfo API expose subscription and customer purchase data programmatically, showing agent-queryable billing state. However, there's no explicit evidence for querying delinquent accounts, upcoming renewals, or per-customer invoice histories via an agent interface. Missing for 10: documented support for delinquency/renewal queries, invoice-level querying, and independent confirmation of Rico's accuracy/scope beyond MRR examples.
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “The CustomerInfo object contains all of the purchase and subscription data available about a customer.”
- [claimed-docs] “RevenueCat charts allow you to understand your user base with key subscription specific metrics, filters, and segments.”
- [github] “See customer transaction histories, chart lifetime value, and grant promotional subscriptions.”
Billing math — stories about billing math in this arenaBilling math
Stories about billing math in this arena
Billing cycles
ops userControl billing anchors and cycles — calendar vs anniversary billing, alignment across a customer's subscriptions, custom invoice dates
weight 2 · round drawnLagonone0/10The evidence pack shows general plan/subscription docs (yearly billing, upgrades/downgrades) but never addresses calendar vs anniversary billing anchors, cross-subscription date alignment, or custom invoice date overrides — the specific billing-math controls this story asks about.
- [claimed-docs] “Yearly: subscription fees are billed on a yearly basis and charges can be billed monthly or annually.”
- [claimed-docs] “In the “Overview” tab, click “Add a plan” on the right”
- [claimed-docs] “Customers have the flexibility to easily upgrade or downgrade their plan at any given moment.”
Proration
finance leadMid-cycle upgrades and downgrades are prorated with documented, auditable math — credits, partial periods, and invoice line items that reconcile to the penny
weight 3 · round to LagoLago documents that customers can upgrade/downgrade plans at any time (lago-docs-4) and has dedicated subscription/plan docs, implying some proration handling, but no evidence shows documented proration formulas, credit line-item detail, or penny-level invoice reconciliation. A community question about upgrade/downgrade tracking (lago-comm-3) goes unanswered in the evidence pack. Missing for 10: explicit proration algorithm documentation, sample invoice line items showing credits/partial periods, and any audit or reconciliation guarantee.
- [claimed-docs] “Customers have the flexibility to easily upgrade or downgrade their plan at any given moment.”
- [claimed-docs] “In the “Overview” tab, click “Add a plan” on the right”
- [community] “User describes building an internal billing tool after bad experiences with Recurly and ChargeBee for B2B/B2E usage-based billing, discounts…”
Dunning recovery — stories about dunning recovery in this arenaDunning recovery
Stories about dunning recovery in this arena
Card recovery
ops userExpiring or replaced cards update themselves — network account updater, backup payment methods, and hosted update-payment pages
weight 2 · round drawnLagonone0/10No evidence in the pack mentions network account updater, backup payment methods, or hosted update-payment pages; Lago's dunning docs focus on invoice/dispute tracking and an AI dunning agent, not card-updating mechanics.
RevenueCatnone0/10RevenueCat's evidence covers subscription management, entitlements, paywalls, MCP/AI tools, and analytics, but nothing addresses card-level dunning recovery mechanics like network account updater, backup payment methods, or hosted update-payment pages — these are Stripe/payment-processor-level features that RevenueCat, as an app-store/subscription management layer, does not document handling itself.
Dunning comms
ops userConfigure automated dunning sequences — branded emails, in-app banners, grace periods, and final-state rules like cancel vs unpaid
weight 2 · round to LagoLago documents dunning-adjacent capabilities: a 'cash-collection' feature to spot overdue/unpaid invoices via filters (lago-docs-13) and a 'Dunning Agent' that reads invoices, payments, disputes, and provider status (lago-docs-10). However, there is no evidence of configurable branded emails, in-app banners, grace periods, or explicit cancel-vs-unpaid final-state rules. Missing for 10: branded email templates, in-app banner UI, grace period configuration, explicit final-state (cancel/unpaid) rule settings, and independent confirmation of the dunning workflow in practice.
- [claimed-docs] “Spot overdue, partially paid or unpaid invoices with filters to never lose track of what you’re owed.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
RevenueCatnone0/10The evidence pack shows RevenueCat's core subscription infrastructure (entitlements, offerings, paywalls, webhooks, exports) but contains no mention of dunning-specific features like branded recovery emails, in-app banners, configurable grace periods, or cancel-vs-unpaid final-state rules. A community comment even requests exactly this kind of timed-notification/dunning hook as a missing feature, reinforcing the absence of evidence for it.
- [community] “Feature request: handling timed hooks to send notifications, e.g. reminding users before a trial expires and subscription cancels.”
- [claimed-docs] “Paywalls — Remotely configure your product offering with powerful paywalls.”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
Smart retries
finance leadFailed renewal payments are retried automatically on an ML- or schedule-optimized cadence that measurably recovers involuntary churn
weight 3 · round to LagoLago documents cash-collection tooling to flag overdue/unpaid invoices and an AI 'Dunning Agent' that reads account history (invoices, payments, disputes, provider status), implying some automated dunning capability, but there is no documented ML- or schedule-optimized retry cadence, no explicit retry logic, and no metrics on churn recovery. Missing for 10: explicit description of automated retry scheduling/cadence optimization, evidence of ML-driven timing, and quantified recovery/churn-reduction outcomes.
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [claimed-docs] “Spot overdue, partially paid or unpaid invoices with filters to never lose track of what you’re owed.”
Entitlements — stories about entitlements in this arenaEntitlements
Stories about entitlements in this arena
Entitlement checks
developerFeatures and limits are modeled as entitlements attached to plans, and my application can check a customer's entitlements at runtime via API or SDK
weight 3 · round to RevenueCatLago has a dedicated entitlements platform page combining billing and feature flags, confirming the concept exists, but the evidence pack contains no detail on how entitlements are attached to plans nor concrete API/SDK examples for runtime entitlement checks. missing for 10: API reference for entitlement endpoints, SDK code samples for checking a customer's entitlements at runtime, plan-to-entitlement modeling details.
- [claimed-docs] “Combine billing and feature flags to avoid bugs and dependencies, reduce complexity and lower and engineering overhead.”
Docs confirm entitlements model access based on purchases without hardcoding product identifiers, and CustomerInfo (via SDK/API, authenticated by API keys) exposes purchase/entitlement data at runtime. This directly matches the story of entitlements attached to plans checked at runtime via SDK/API. Missing for 10: explicit code snippet showing an entitlement check call and independent/hands-on developer confirmation of the runtime check pattern.
- [claimed-docs] “Entitlements are used to ensure a user has appropriate access to content based on their purchases, without having to manage all of the produ…”
- [claimed-docs] “The CustomerInfo object contains all of the purchase and subscription data available about a customer.”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [github] “Fetch products, make purchases, and check subscription status with our native SDKs.”
Plan versioning
ops userChange pricing without breaking existing subscribers — versioned plans, grandfathering, and bulk migration tools for moving cohorts to new prices
weight 2 · round to LagoDocs show basic plan/subscription management (assign plan, upgrade/downgrade) but no explicit mention of plan versioning, grandfathering existing subscribers, or bulk cohort migration tools. missing for 10: explicit versioned-plan mechanism, grandfathering documentation, bulk/cohort migration tooling or API endpoints.
- [claimed-docs] “In the “Overview” tab, click “Add a plan” on the right”
- [claimed-docs] “Customers have the flexibility to easily upgrade or downgrade their plan at any given moment.”
- [claimed-docs] “Yearly: subscription fees are billed on a yearly basis and charges can be billed monthly or annually.”
RevenueCatnone0/10While RevenueCat's Offerings/Packages system (revenuecat-docs-8) implies some product versioning, there is no evidence of price-specific grandfathering, versioned pricing plans, or bulk cohort migration tools; the only 'migration' documentation (revenuecat-docs-4) concerns importing existing purchase data when onboarding to RevenueCat, not moving cohorts between price tiers post-launch. This is a fair capability to expect from a subscription billing platform, so the axis applies, but no concrete evidence supports it.
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
- [claimed-docs] “Importing existing purchase data to RevenueCat can be done server-side, or client-side.”
Invoicing tax — stories about invoicing tax in this arenaInvoicing tax
Stories about invoicing tax in this arena
Invoices
ops userThe platform generates compliant invoices, credit notes, and receipts — sequential numbering, custom fields, memos — delivered to customers automatically
weight 2 · round to LagoLago's docs confirm core invoicing functionality (downloadable invoices, customizable invoice templates) and cash-collection tracking of overdue invoices, showing invoicing is a first-class feature, but the evidence pack contains no mention of credit notes, receipts, sequential numbering, custom fields, or memos, nor confirmation of fully automated delivery to customers. missing for 10: credit note support, receipt generation, sequential invoice numbering, custom fields/memos on invoices, automatic delivery mechanism confirmation.
- [claimed-docs] “You can download invoices or use the invoice object to create your own invoice template.”
- [claimed-docs] “Spot overdue, partially paid or unpaid invoices with filters to never lose track of what you’re owed.”
Multi currency
finance leadBill customers in their local currency with per-currency price points and consolidated reporting in my home currency
weight 2 · round drawnLagonone0/10No evidence in the pack addresses multi-currency billing, per-currency price points, or consolidated home-currency reporting; docs cover plans, invoicing, dunning, and revenue analytics but never mention currency handling or FX consolidation. Missing for 10: any documentation of multi-currency price points, currency conversion/consolidation logic, and reporting rollups in a base currency.
RevenueCatnone0/10No evidence describes local-currency price points, per-currency pricing configuration, or consolidated home-currency reporting; the evidence pack covers entitlements, paywalls, SDKs, MCP tools, and dashboards but nothing about multi-currency billing or currency-consolidated financial reports.
Tax
finance leadSales tax, VAT, and GST are calculated on every invoice — natively or through a first-class tax integration — with the right registrations and rates
weight 2 · round drawnLagonone0/10No evidence pack item mentions tax calculation, VAT/GST/sales tax handling, tax registrations, tax rates, or integrations with tax engines (e.g., Avalara, Stripe Tax, TaxJar). The docs cover invoicing, plans, subscriptions, and dunning but never address tax compliance. Missing for 10: any mention of native tax calculation, tax rate/registration management, or a first-class tax-engine integration.
RevenueCatnone0/10No evidence RevenueCat calculates or manages sales tax, VAT, or GST, nor any mention of tax registrations, rates, or a tax integration; RevenueCat's role for App Store/Play purchases means Apple/Google handle tax, and no tax-handling capability is documented for its own billing (e.g., Stripe-side) invoicing.
Migration portability — stories about migration portability in this arenaMigration portability
Stories about migration portability in this arena
Export
finance leadExport every subscription, invoice, and usage record — and port stored payment methods out to another provider — if I choose to leave
weight 2 · round drawnLago's API/OpenAPI schema and CSV export for analytics (lago-docs-15, lago-docs-16, lago-docs-1) mean a finance lead could theoretically pull subscription, invoice, and usage data out via API, and self-hosting (lago-docs-11) avoids lock-in of infrastructure. However, there is no documented bulk-export or migration tool, no explicit invoice/subscription/usage-record export workflow, and payment methods are held by external providers (Stripe etc.) rather than Lago itself, so 'porting stored payment methods' isn't addressed at all. Missing for 10: dedicated data-export/migration documentation, explicit payment-method portability mechanism, and any hands-on evidence of a successful migration off Lago.
- [claimed-docs] “Build custom dashboards per customer, filter any way you want and export to CSV.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “You can download invoices or use the invoice object to create your own invoice template.”
- [claimed-docs] “Docker is the easiest way to get started with the self-hosted version of Lago.”
RevenueCat offers scheduled data exports to cloud storage/email and REST API access to customer/subscription data (docs-7, docs-5, docs-3), which covers some of the 'export subscriptions/customer records' need. However, there is no evidence of invoice-level or usage-record export, and no mention anywhere of porting stored payment methods to another provider — RevenueCat itself doesn't store card details (they live with Stripe/Apple/Google), so this key part of the story is unaddressed. Community discussion even flags that migrating subscriptions between providers is 'hard to make smooth' (revenuecat-comm-8), reinforcing the gap. Missing for 10: documented invoice/usage export, explicit payment-method portability/export mechanism, and confirmation of smooth cross-provider migration.
- [claimed-docs] “RevenueCat delivers your apps' data to a cloud storage provider or to email on a schedule you control.”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “The CustomerInfo object contains all of the purchase and subscription data available about a customer.”
- [community] “User considering migrating to RevenueCat asks whether it can handle users moving subscriptions between iOS/Android in-app purchases and Stri…”
Import
ops userMigrate live subscriptions in from a spreadsheet or a competing platform — including PCI-compliant card data transfer — without customers noticing
weight 3 · round to RevenueCatLagonone0/10No evidence in the pack describes any migration tooling, bulk-import from spreadsheets, or PCI-compliant card-data transfer capability; the API/docs cover plan assignment and event ingestion but nothing about importing live subscriptions from another platform. Community comments even suggest Lago does not itself handle payment/PCI processing (lago-comm-8), reinforcing the absence of this capability.
- [community] “"If I still have to pay the processing fees, what's the advantage here? Having to maintain my own payments stack (and PCI compliance) sounds…”
RevenueCat explicitly documents importing existing purchase/subscription data 'server-side or client-side' when migrating to the platform, which supports the core migration story, but there is no evidence describing spreadsheet-based import, PCI-compliant card data transfer, or explicit guarantees that migration is invisible to end customers. Community comments (revenuecat-comm-8, revenuecat-comm-3) show users actively wondering whether smooth cross-platform migration (App Store/Stripe) is even possible, indicating this remains an open question rather than a proven capability. missing for 10: PCI-compliant card data transfer mechanics, spreadsheet import tooling, documented zero-customer-disruption guarantee, and independent confirmation of smooth migration.
- [claimed-docs] “Importing existing purchase data to RevenueCat can be done server-side, or client-side.”
- [community] “User considering migrating to RevenueCat asks whether it can handle users moving subscriptions between iOS/Android in-app purchases and Stri…”
- [community] “"Man I wish this existed 8 months ago when I built our own version internally! We have a mix of Stripe and App Store customers so we'll defi…”
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 to LagoLago's docs show an API-first design: every endpoint has a generated CLI/code sample (lago-docs-1), a full OpenAPI 3.1 schema is available (lago-docs-16, lago-probe-3), and specific UI actions like usage-charge updates are explicitly available via both API and no-code UI (lago-docs-14). This implies strong API/UI parity but there is no explicit vendor claim or independent audit confirming 100% parity across every UI workflow (e.g., dunning, revenue analytics dashboards). missing for 10: an explicit 'everything in the UI is available via API' statement, and independent/community confirmation of full parity across all UI features.
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “Both non-engineers and engineers can update usage charges via API or Lago’s no-code UI.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
RevenueCat documents a REST API/authentication (revenuecat-docs-5), an MCP server that lets AI assistants manage apps, Products, Entitlements 'without using the RevenueCat dashboard' (revenuecat-docs-9), and an AI toolkit for setting up subscriptions, offerings, and packages (revenuecat-docs-8), showing strong API parity for core configuration tasks. However, no OpenAPI spec was discoverable (revenuecat-probe-3) and UI-centric features like paywall design, charts, and dashboard-and-metrics exploration appear tied to the dashboard or scheduled exports rather than full API control (revenuecat-docs-6, revenuecat-docs-7, revenuecat-docs-11). Missing for 10: publicly documented OpenAPI/full REST API reference, evidence that paywall building/analytics dashboards are fully API-accessible, and independent confirmation of complete UI-API parity.
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “RevenueCat charts allow you to understand your user base with key subscription specific metrics, filters, and segments.”
- [claimed-docs] “Paywalls — Remotely configure your product offering with powerful paywalls.”
- [probe] “PROBE openapi: all candidate paths 404 (https://www.revenuecat.com/openapi.json, https://www.revenuecat.com/swagger.json, https://www.revenu…”
ai-native userExport all of my data in open formats and leave
weight 3 · round to LagoLago's open-source/self-hosted nature (Docker deployment), open API (OpenAPI 3.1 schema, full REST reference), and CSV export of analytics/invoices give users real data-portability levers, and self-hosting means the underlying database is always in the user's own control. However there is no documented single 'export all account data' or account-closure/migration feature — only piecemeal exports (invoices, revenue analytics CSV, API access to individual objects). Missing for 10: a dedicated full-account data export/backup tool, explicit data-portability/migration documentation, and independent confirmation of a clean 'leave' workflow.
- [claimed-docs] “Docker is the easiest way to get started with the self-hosted version of Lago.”
- [claimed-docs] “You can download invoices or use the invoice object to create your own invoice template.”
- [claimed-docs] “Build custom dashboards per customer, filter any way you want and export to CSV.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
RevenueCat does support scheduled data exports to cloud storage/email and a REST API for programmatic access to customer/subscription data, giving some data portability. However, there's no documented comprehensive 'export all your data and leave' feature, no explicit open-format full account export, and no OpenAPI spec found (probe returned 404s). Missing for 10: a documented full-account data export/deletion workflow, explicit open-format guarantees, and confirmation of a public OpenAPI/schema for complete data extraction.
- [claimed-docs] “RevenueCat delivers your apps' data to a cloud storage provider or to email on a schedule you control.”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [probe] “PROBE openapi: all candidate paths 404 (https://www.revenuecat.com/openapi.json, https://www.revenuecat.com/swagger.json, https://www.revenu…”
ai-native userRead the product's source under an open license
weight 2 · round to LagoLago's docs and GitHub explicitly describe it as an open-source billing platform with a public source repository (getlago/lago), and the llms.txt probe confirms this framing, satisfying the 'read source under open license' story. Missing for 10: explicit citation of the specific license name/file (e.g., AGPL) and independent verification of license terms beyond the 'open-source' label.
RevenueCat publishes open-source client SDKs on GitHub (e.g., purchases-ios) showing feature code, but the evidence never states a specific open-source license nor shows the core backend/platform source, which remains a closed SaaS product. missing for 10: explicit license statement, evidence of core platform/service source being open, independent confirmation of license terms.
- [github] “Fetch products, make purchases, and check subscription status with our native SDKs.”
- [github] “Host and configure products remotely from our dashboard.”
- [github] “Get notified of real-time events through webhooks.”
- [github] “See customer transaction histories, chart lifetime value, and grant promotional subscriptions.”
ai-native userSelf-host the core product
weight 3 · round to LagoDocs explicitly cover self-hosting via Docker with a dedicated guide, and community comments confirm self-hosting is a real, used option ('self-hosting is not an issue', 'a self-hosted option fits our culture'). Missing for 10: independent hands-on report of running the full self-hosted stack in production, and more detail on self-hosted feature parity/limitations vs cloud.
- [claimed-docs] “Docker is the easiest way to get started with the self-hosted version of Lago.”
- [community] “"This looks great... Stripe is awesome but a self-hosted option fits our culture and philosophy a lot better. Will give it a blast when i ge…”
- [community] “"Looks very interesting. We are small shop and self-hosting is not an issue. This neatly fits a requirement we've had for quite some time."”
RevenueCatnone0/10RevenueCat is delivered purely as a hosted SaaS platform (dashboard, cloud APIs, webhooks, MCP server) with no mention of an on-premises or self-hosted deployment option anywhere in the evidence pack; community discussion even treats it as an external service to 'switch to' rather than something to run locally. Missing for 10: any documentation of self-hosted/on-prem deployment, open-source core, or Docker/Kubernetes packaging.
- [probe] “PROBE llms.txt: HTTP 200 at https://www.revenuecat.com/llms.txt # RevenueCat > RevenueCat is the App Monetization OS for mobile and web app…”
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [community] “User asks why use RevenueCat over Stripe, which is developer-friendly, robust, and unlikely to disappear.”
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 to LagoLago's self-hosted Docker deployment (lago-docs-11) implicitly lets a user control where their data resides by choosing their own infrastructure/region, but there is no explicit documentation of a region-selection feature, data-residency guarantees, or compliance certifications for the managed/cloud offering. missing for 10: explicit data-residency/region-selection feature docs, compliance certifications (e.g., GDPR/SOC2 region controls), managed-cloud region options.
- [claimed-docs] “Docker is the easiest way to get started with the self-hosted version of Lago.”
ai-native userControl data retention and deletion
weight 2 · round drawnLagonone0/10No evidence in the pack addresses data retention policies, deletion of customer/billing data, or GDPR-style controls; Lago's docs focus on billing, invoicing, and AI agent features but never mention data retention/deletion controls. Missing for 10: documentation on data retention windows, customer data deletion/export mechanisms, and any privacy/GDPR compliance controls.
ai-native userOpt out of telemetry and usage tracking
weight 2 · round drawnLagonone0/10No evidence in the pack addresses telemetry, usage tracking, or opt-out settings for Lago itself (self-hosted or cloud). The docs cover billing features, AI agents, and self-hosting setup, but nothing about product analytics/telemetry collection or a way to disable it. Missing for 10: any mention of telemetry collection, an opt-out flag/config, or privacy documentation addressing data sent back to Lago.
Revenue recognition — stories about revenue recognition in this arenaRevenue recognition
Stories about revenue recognition in this arena
Analytics
founderI get MRR, churn, cohort retention, and LTV analytics computed from the billing source of truth, not a bolted-on BI export
weight 2 · round to RevenueCatLagonone0/10Lago's docs mention a generic 'revenue-analytics' page with custom dashboards, filters, and CSV export (lago-docs-15), which is closer to the bolted-on BI export the story explicitly wants to avoid, not native MRR/churn/cohort-retention/LTV computation. No evidence pack item shows Lago computing these specific metrics natively from billing data, and a community question in lago-comm-3 explicitly asks whether Lago handles revenue recognition, left unanswered.
- [claimed-docs] “Build custom dashboards per customer, filter any way you want and export to CSV.”
- [community] “User describes building an internal billing tool after bad experiences with Recurly and ChargeBee for B2B/B2E usage-based billing, discounts…”
RevenueCat's dashboard/charts and Rico assistant explicitly surface MRR and LTV computed directly from subscription/billing events (revenuecat-docs-6, revenuecat-docs-10, revenuecat-gh-4), and scheduled exports let founders pull this data (revenuecat-docs-7), all sourced from the billing data rather than a bolted-on BI tool. However, the evidence pack never explicitly mentions churn metrics or cohort retention analysis by name, so the story's full metric set isn't documented. Missing for 10: explicit churn-rate analytics, explicit cohort retention analytics/reporting.
- [claimed-docs] “RevenueCat charts allow you to understand your user base with key subscription specific metrics, filters, and segments.”
- [claimed-docs] “Instead of digging through charts and tables yourself, you can ask Rico plain-language questions like "Why did MRR drop in Germany last week…”
- [github] “See customer transaction histories, chart lifetime value, and grant promotional subscriptions.”
- [claimed-docs] “RevenueCat delivers your apps' data to a cloud storage provider or to email on a schedule you control.”
Gl sync
finance leadInvoices, payments, and recognition entries sync to my general ledger or ERP — QuickBooks, Xero, NetSuite — so the close doesn't need CSV surgery
weight 2 · round drawnLagonone0/10The evidence pack shows Lago's API, webhooks, invoicing, and OpenAPI schema, but there is no mention of any native or partner integration with QuickBooks, Xero, or NetSuite, nor any revenue-recognition export/sync to a GL/ERP system. Finance-lead close automation is a fair axis for a billing platform, but nothing in the pack demonstrates it.
Revrec reports
finance leadRevenue is recognized on an ASC 606 / IFRS 15 basis — deferred revenue schedules and audit-ready recognition reports straight from billing data
weight 3 · round drawnLagonone0/10No evidence describes ASC 606/IFRS 15 deferred revenue schedules or audit-ready recognition reports; the closest material (revenue-analytics dashboards/CSV export) is generic reporting, not recognition accounting. A community comment even explicitly asks whether Lago handles revenue recognition, with no documented answer.
- [claimed-docs] “Build custom dashboards per customer, filter any way you want and export to CSV.”
- [community] “User describes building an internal billing tool after bad experiences with Recurly and ChargeBee for B2B/B2E usage-based billing, discounts…”
RevenueCatnone0/10Evidence covers subscription SDKs, entitlements, charts, and data exports, but nothing addresses ASC 606/IFRS 15 deferred revenue schedules or audit-ready recognition reporting. Missing for 10: any mention of deferred revenue calculation, revenue recognition compliance, or audit-ready financial reports.
Subscription lifecycle — stories about subscription lifecycle in this arenaSubscription lifecycle
Stories about subscription lifecycle in this arena
Lifecycle api
developerCreate, update, pause, and cancel subscriptions through a documented API — the full lifecycle without touching a dashboard
weight 3 · round to LagoLago's docs cover API-driven subscription creation (assign-plan), upgrades/downgrades, and a full OpenAPI 3.1 schema with generated commands per endpoint, supporting a documented API lifecycle. However, the evidence pack never explicitly documents pause or cancel subscription endpoints, and most subscription guides (e.g., assign-plan) describe dashboard clicks rather than pure API-only flows. Missing for 10: explicit pause/cancel endpoint documentation, and hands-on/independent confirmation that the entire lifecycle can be done via API without the dashboard.
- [claimed-docs] “Every endpoint in this reference has a generated command.”
- [claimed-docs] “In the “Overview” tab, click “Add a plan” on the right”
- [claimed-docs] “Customers have the flexibility to easily upgrade or downgrade their plan at any given moment.”
- [claimed-docs] “Use Lago's OpenAPI 3.1 schema to generate clients, inspect typed operations, or expose billing actions to an AI agent.”
- [probe] “PROBE openapi: HTTP 200 at https://getlago.com/openapi.json — contains "openapi" key”
RevenueCat exposes API-based mechanisms for parts of subscription management (granting promotional subscriptions via API/dashboard, managing Products/Entitlements/Offerings via the AI toolkit and MCP server 'without using the dashboard'), and confirms REST API authentication exists. However, there's no direct evidence of documented endpoints to create, update, pause, or cancel a live subscription's lifecycle end-to-end, and a probe for OpenAPI/swagger docs returned 404s, suggesting the full API surface isn't publicly documented in this pack. missing for 10: explicit API endpoints for pause/cancel/update, a discoverable OpenAPI spec, and confirmation that full lifecycle actions (not just entitlement grants/catalog config) can be done purely via API.
- [claimed-docs] “RevenueCat authenticates requests from the RevenueCat SDK and the REST API using API keys.”
- [claimed-docs] “Set up subscriptions, including projects, apps, Products, Entitlements, Offerings, and Packages”
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
- [github] “See customer transaction histories, chart lifetime value, and grant promotional subscriptions.”
- [probe] “PROBE openapi: all candidate paths 404 (https://www.revenuecat.com/openapi.json, https://www.revenuecat.com/swagger.json, https://www.revenu…”
Lifecycle events
developerEvery subscription state change — renewal, upgrade, payment failure, cancellation — emits a webhook or event my systems can act on reliably
weight 2 · round to LagoLago documents a webhook system with signing (HMAC) and explicitly treats 'webhook event types' as a versioned API surface, implying granular event types exist, but the evidence never enumerates specific subscription lifecycle events (renewal, upgrade, payment failure, cancellation) or demonstrates delivery reliability guarantees like retries/idempotency for webhooks specifically. missing for 10: explicit list/documentation of subscription lifecycle event types, evidence of webhook delivery reliability (retries, dead-letter, idempotency) beyond event-ingestion dedup which is a different feature.
- [claimed-docs] “The second is `HMAC`, which features a shorter payload header and no size restrictions.”
- [claimed-docs] “Clients should tolerate additive changes within v1, including new response fields, enum values, endpoints, optional request fields, and webh…”
RevenueCat explicitly advertises real-time webhook events (revenuecat-gh-3) and dashboard/customer-info data on subscription state (revenuecat-docs-3), supporting the general claim that lifecycle changes are exposed as events. However, the evidence pack lacks detail on which specific lifecycle events (renewal, upgrade, payment failure, cancellation) are covered, delivery guarantees/retries, or reliability at scale, and a community request for additional timed hooks (revenuecat-comm-6) suggests some lifecycle notifications are still missing today. Missing for 10: documented list of webhook event types, delivery/retry guarantees, and evidence of reliability under real-world load.
- [github] “Get notified of real-time events through webhooks.”
- [claimed-docs] “The CustomerInfo object contains all of the purchase and subscription data available about a customer.”
- [community] “Feature request: handling timed hooks to send notifications, e.g. reminding users before a trial expires and subscription cancels.”
Self serve
founderMy customers can upgrade, downgrade, or cancel themselves through a hosted portal or embeddable components, without a support ticket
weight 2 · round drawnLagonone0/10Evidence confirms upgrade/downgrade functionality exists (lago-docs-4, lago-docs-3) but only via API or Lago's internal admin UI — there is no mention anywhere in the pack of a customer-facing hosted portal or embeddable self-serve components that end customers could use directly. Community comments even question whether Lago handles full self-serve lifecycle (lago-comm-3), and nothing confirms a portal exists.
- [claimed-docs] “Customers have the flexibility to easily upgrade or downgrade their plan at any given moment.”
- [claimed-docs] “In the “Overview” tab, click “Add a plan” on the right”
- [community] “User describes building an internal billing tool after bad experiences with Recurly and ChargeBee for B2B/B2E usage-based billing, discounts…”
RevenueCatnone0/10The evidence covers RevenueCat's SDKs, entitlements, paywalls, and dashboard analytics, but nothing describes a hosted customer portal or embeddable UI components letting end customers upgrade/downgrade/cancel without a support ticket. Community threads even discuss the difficulty of managing cross-platform (iOS/Android/Stripe) subscription moves, but no resolution or feature is cited that gives self-service cancellation/upgrade capability.
- [claimed-docs] “Paywalls — Remotely configure your product offering with powerful paywalls.”
- [community] “User considering migrating to RevenueCat asks whether it can handle users moving subscriptions between iOS/Android in-app purchases and Stri…”
- [community] “Feature request: handling timed hooks to send notifications, e.g. reminding users before a trial expires and subscription cancels.”
Trials promos
ops userRun free trials, coupons, and promotion codes with automatic conversion to paid — including trial-end notifications required by card-network rules
weight 2 · round to RevenueCatLagonone0/10No evidence pack items mention free trials, coupons, promotion codes, automatic trial-to-paid conversion, or trial-end notifications required by card-network rules; evidence covers plans, subscriptions, invoicing, webhooks, and AI agents but not this trial/coupon lifecycle. missing for 10: docs on free trials, coupons/promo codes, automatic conversion to paid, and trial-end notification compliance.
RevenueCat supports free-trial eligibility checks, entitlements, and granting promotional subscriptions, and webhooks could be used to build custom trial-reminder logic, but there is no documented native coupon/promo-code management or built-in trial-end notification feature — in fact a community post explicitly requests this as a missing feature ('handling timed hooks to send notifications... reminding users before a trial expires'). missing for 10: native coupon/promo-code support, built-in trial-end notification delivery, card-network compliance documentation.
- [claimed-docs] “The Purchases SDK allows for easy checking of eligibility for introductory offers on iOS, so that you as the developer can display the prope…”
- [github] “See customer transaction histories, chart lifetime value, and grant promotional subscriptions.”
- [github] “Get notified of real-time events through webhooks.”
- [community] “Feature request: handling timed hooks to send notifications, e.g. reminding users before a trial expires and subscription cancels.”
Usage metering — stories about usage metering in this arenaUsage metering
Stories about usage metering in this arena
Event ingestion
developerStream high-volume usage events — API calls, tokens, compute-seconds — into a metering pipeline with idempotent ingestion and backdating support
weight 3 · round to LagoLago's docs confirm idempotent event ingestion (dedup on repeated event IDs) and a usage-metering pipeline supporting API-driven event updates, which covers the core ingestion/idempotency claims. However, there is no explicit evidence of backdating support (e.g., specifying a past timestamp for events) or of high-volume streaming architecture/throughput guarantees for API calls, tokens, or compute-seconds use cases. missing for 10: explicit backdating/timestamp-override documentation, evidence of high-volume/streaming ingestion architecture or throughput benchmarks, independent verification of dedup behavior at scale.
- [claimed-docs] “Lago uses it for deduplication: if the same event arrives twice, it is billed once.”
- [claimed-docs] “Both non-engineers and engineers can update usage charges via API or Lago’s no-code UI.”
RevenueCatnone0/10RevenueCat is a subscription/purchase management platform focused on entitlements, offerings, and billing data — nothing in the evidence describes streaming high-volume usage events (API calls, tokens, compute-seconds) with idempotent ingestion or backdating support, which is a usage-based metering capability outside RevenueCat's documented scope.
- [claimed-docs] “The CustomerInfo object contains all of the purchase and subscription data available about a customer.”
- [claimed-docs] “Importing existing purchase data to RevenueCat can be done server-side, or client-side.”
- [claimed-docs] “RevenueCat charts allow you to understand your user base with key subscription specific metrics, filters, and segments.”
- [probe] “PROBE llms.txt: HTTP 200 at https://www.revenuecat.com/llms.txt # RevenueCat > RevenueCat is the App Monetization OS for mobile and web app…”
Pricing models
finance leadPrice with tiered, volume, graduated, per-unit, and hybrid subscription-plus-usage models — including credits, commitments, and overage — without custom code
weight 3 · round to LagoLago's own positioning ('usage-based, subscription-based, and hybrid pricing models') and the plan-model/usage-metering docs confirm broad subscription+usage flexibility, and community reviews praise it for handling complex billing without custom code, but the evidence pack never explicitly documents tiered, volume, graduated, or per-unit charge models, nor credits, commitments, or overage handling as distinct configurable features. missing for 10: explicit docs on tiered/volume/graduated/per-unit charge model configuration, credits and commitment mechanics, overage billing rules, and independent confirmation these work without custom code.
- [probe] “PROBE llms.txt: HTTP 200 at https://getlago.com/llms.txt # Lago > Lago is the open-source billing platform for usage-based, subscription-ba…”
- [claimed-docs] “Yearly: subscription fees are billed on a yearly basis and charges can be billed monthly or annually.”
- [claimed-docs] “Both non-engineers and engineers can update usage charges via API or Lago’s no-code UI.”
- [claimed-docs] “Spot overdue, partially paid or unpaid invoices with filters to never lose track of what you’re owed.”
- [community] “"We decided to use Lago with our SaaS. Billing is super complicated and Lago handles everything we need out of the box. Building this stuff …”
- [community] “"Lago is awesome. We'll likely use Lago at my startup (metlo) when we implement full self-serve usage-based billing."”
RevenueCatnone0/10RevenueCat's evidence covers mobile subscription entitlements, offerings, paywalls, and analytics, but there is no mention of tiered/volume/graduated/per-unit pricing, usage-based billing, credits, commitments, or overage handling — the core usage-metering pricing models in the story are entirely absent.
Usage visibility
ops userCustomers and my team can see current-cycle usage and accrued cost in real time, with thresholds and alerts before an invoice surprises anyone
weight 2 · round to LagoLago documents usage-metering and customer-facing analytics dashboards (lago-docs-14, lago-docs-15) and webhooks for event notifications (lago-docs-7), which could support real-time usage visibility, but there is no explicit documentation of configurable usage thresholds or proactive alerting before invoice generation. missing for 10: explicit threshold/alert configuration feature, evidence of real-time cost accrual view distinct from dashboards, confirmation that customers (not just ops) see live usage/cost.
- [claimed-docs] “Both non-engineers and engineers can update usage charges via API or Lago’s no-code UI.”
- [claimed-docs] “Build custom dashboards per customer, filter any way you want and export to CSV.”
- [claimed-docs] “The second is `HMAC`, which features a shorter payload header and no size restrictions.”
Not comparable on these axes
ai-native userPlug MCP servers into this product so it can use their tools
weight 3 · not comparableLagonone0/10The evidence shows Lago exposes its own MCP server so external AI assistants can access Lago's billing data (lago-docs-9, lago-probe-4) and has AI agents (Dunning Agent) that read Lago's own account data (lago-docs-10) — this is Lago acting as an MCP server/tool provider, not as a client that plugs in external MCP servers to gain new tools. No evidence shows Lago's agents or platform consuming/connecting to third-party MCP servers.
- [claimed-docs] “provides AI assistants (like Claude) with direct access to Lago’s billing data.”
- [claimed-docs] “The Dunning Agent reads the account first: twelve months of invoices and payments, the disputes, the provider status.”
- [probe] “official MCP server documented at https://getlago.com/docs/guide/ai-agents/mcp-server”
RevenueCatn/aRevenueCat is a subscription/monetization backend platform, not an AI agent or assistant that a user interacts with and extends via plugged-in MCP servers. The evidence shows RevenueCat ships its OWN MCP server (revenuecat-docs-9) so that external AI assistants can call RevenueCat's tools — this is the server role, the opposite of the client-side 'plug servers into this product' story, so the axis is a category mismatch here.
- [claimed-docs] “The RevenueCat MCP (Model Context Protocol) server enables AI assistants to manage subscription apps, Products, Entitlements, and everything…”
ai-native userVersion, review, and roll back my automations
weight 1 · not comparableLagon/aLago is a billing platform, not an automation/workflow builder; there is no concept of 'automations' with versioning, review, or rollback in the evidence pack. This axis is a category error for this product.
ai-native userPrevent my data from being used to train AI models
weight 3 · not comparableLagonone0/10Lago is a billing platform; evidence covers billing, invoicing, self-hosting, and AI agent integrations (MCP server, dunning agent) but nowhere addresses data-use-for-AI-training opt-outs or privacy controls over model training. Missing for 10: any privacy policy statement, opt-out mechanism, or data-training exclusion clause.