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Posthog

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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.

PublisherPostHog
Repositoryposthog
LanguagePython
Forks
3.5K
Stars
40K
Available tools
0
Transport typestdio
Links
GitHubHomepage
  • Connect tools to AI workflows

    Posthog exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    40K stars and 3.5K forks from the linked repository.

PostHog is the open source platform for building self-driving products

PostHog provides every tool you need to build a successful product, and captures all the context agents need to proactively diagnose problems, uncover opportunities, and ship fixes:

  • Self-driving mode: Turn signals in your product data (errors, rage clicks, failed queries, and more) into researched reports and pull requests you review and merge.
  • Product analytics: Autocapture or manually instrument event-based analytics to understand user behavior and analyze data with visualization or SQL.
  • Web analytics: Monitor web traffic and user sessions with a GA-like dashboard. Easily monitor conversion, web vitals, and revenue.
  • Session replays: Watch real user sessions of interactions with your website or mobile app to diagnose issues and understand user behavior.
  • Feature flags: Safely roll out features to select users or cohorts with feature flags.
  • Experiments: Test changes and measure their statistical impact on goal metrics. Set up experiments with no-code too.
  • Error tracking: Track errors, get alerts, and resolve issues to improve your product.
  • Logs: Ingest, search, and analyze log data alongside the rest of your product data.
  • Surveys: Ask anything with our collection of no-code survey templates, or build custom surveys with our survey builder.
  • Data warehouse: Sync data from external tools like Stripe, Hubspot, your data warehouse, and more. Query it alongside your product data.
  • Data pipelines: Run custom filters and transformations on your incoming data. Send it to 25+ tools or any webhook in real time or batch export large amounts to your warehouse.
  • AI observability: Capture traces, generations, latency, and cost for your LLM-powered app.
  • Workflows: Create workflows that automate actions or send messages to your users.

You can steer it all from Slack, web, desktop (PostHog Desktop), or your own editor via the MCP.

Best of all, all of this is free to use with a generous monthly free tier for each tool. Get started by signing up for PostHog Cloud US or PostHog Cloud EU.

Table of Contents

Getting started with PostHog

PostHog Cloud (Recommended)

The fastest and most reliable way to get started with PostHog is signing up for free to PostHog Cloud or PostHog Cloud EU. Your first 1 million events, 5k recordings, 1M flag requests, 100k exceptions, and 1500 survey responses are free every month, after which you pay based on usage.

Self-hosting the open-source hobby deploy (Advanced)

If you want to self-host PostHog, you can deploy a hobby instance in one line on Linux with Docker (recommended 4GB memory):

bash
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/posthog/posthog/HEAD/bin/deploy-hobby)"

Open source deployments should scale to approximately 100k events per month, after which we recommend migrating to a PostHog Cloud.

We do not provide customer support or offer guarantees for open source deployments. See our self-hosting docs, troubleshooting guide, and disclaimer for more info.

Setting up PostHog

Once you've got a PostHog instance, you can set it up by installing our JavaScript web snippet, one of our SDKs, or by using our API. You can also connect the MCP to bring PostHog into Claude Code, Cursor, or any MCP-compatible agent.

We have SDKs and libraries for popular languages and frameworks like:

FrontendMobileBackend
JavaScriptReact NativePython
Next.jsAndroidNode
ReactiOSPHP
VueFlutterRuby

Beyond this, we have docs and guides for Go, .NET/C#, Django, Angular, WordPress, Webflow, and more.

Once you've installed PostHog, see our product docs for more information on how to set up product analytics, web analytics, session replays, feature flags, experiments, error tracking, surveys, data warehouse, and more.

Learning more about PostHog

Our code isn't the only thing that's open source 😳. We also open source our company handbook which details our strategy, ways of working, and processes.

Curious about how to make the most of PostHog? We wrote a guide to winning with PostHog which walks you through the basics of measuring activation, tracking retention, and capturing revenue.

Contributing

We <3 contributions big and small:

For an overview of the codebase structure, see monorepo layout and products.

Open-source vs. paid

This repo is available under the MIT expat license, except for the ee directory (which has its license here) if applicable.

Need absolutely 💯% FOSS? Check out our posthog-foss repository, which is purged of all proprietary code and features.

The pricing for our paid plan is completely transparent and available on our pricing page.

We're hiring!

Hey! If you're reading this, you've proven yourself as a dedicated README reader.

You might also make a great addition to our team. We're growing fast and would love for you to join us.

Use Posthog MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Posthog is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Posthog as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Posthog MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "posthog": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Posthog MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Posthog MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Posthog to help me with this task?
Posthog
Sure. I read it.
Here is what I found using Posthog.

Frequently asked questions

What is the Posthog MCP server used for?

Posthog is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Posthog MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Posthog with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Posthog MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Posthog connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Posthog MCP to TypingMind?

Posthog runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Posthog MCP provide in TypingMind?

Posthog exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Posthog MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Posthog requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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