Ross ROSS = Recommend OSS · open-source software intelligence for agents

PostHog

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP. observed · 2026-08-28

github.com/PostHog/posthog · homepage · Python · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

95/100

  • Activity 99
  • Release rhythm 87
  • Longevity 100

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 0
  • age_days: 2414
  • days_rel: 6
  • days_push: 7
  • n_releases_24m: 948

Full methodology

Adoption not part of the score

39256 stars · 3291 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

PostHog is an open-source product analytics platform combining product analytics, web analytics, session replay, feature flags, A/B experiments, error tracking, logs, surveys, and a customer data platform in one self-hostable or cloud-hosted suite. It also offers AI observability and 'self-driving' capabilities that turn product data signals into researched reports and pull requests, controllable via Slack, web, desktop, or MCP.

Use cases

  • track user behavior with event-based product analytics
  • watch session replays to debug UX issues
  • roll out features gradually with feature flags
  • run A/B tests and measure statistical impact
  • monitor web traffic and conversion funnels
  • track and alert on application errors
  • self-host a Google Analytics alternative
  • analyze product data with SQL

When to choose

  • you want an all-in-one analytics, flags, and replay platform you can self-host
  • you need autocapture analytics without manual instrumentation
  • you want feature flags and experiments tightly integrated with analytics
  • you need AI observability for LLM-powered products

When to avoid

  • you only need lightweight page-view counting without a data pipeline
  • you cannot operate a resource-heavy Python/Docker stack and don't want the cloud offering
  • you need strict per-event data residency controls the platform doesn't support

Facets

application · maturity active

analytics monitoring alerting feature-flags data-visualization error-handling logging mcp chatbot analytics developer-tools web-development artificial-intelligence self-hosted self-hosted python product-analytics session-replay feature-flags ab-testing web-analytics surveys data-warehouse cdp ai-observability self-driving-products web-server docker javascript web

2 sources

Member repositories

RepositoryRoleHealth v2
PostHog/posthogmain95
PostHog/posthog.comdocs77

For agents

markdown · JSON · MCP: product_card(name="PostHog/posthog")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem