PostHog MCP
Enables interaction with PostHog's product analytics platform through natural language, allowing users to manage feature flags, view errors, and access other platform features.
README
PostHog MCP
Use the MCP Server
Quick install
You can install the MCP server automatically into popular clients by running the following command:
npx @posthog/wizard@latest mcp add
Manual install
-
Obtain a personal API key using the MCP Server preset here.
-
Add the MCP configuration to your desktop client (e.g. Cursor, Windsurf, Claude Desktop) and add your personal API key
{
"mcpServers": {
"posthog": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://mcp.posthog.com/sse",
"--header",
"Authorization:${POSTHOG_AUTH_HEADER}"
],
"env": {
"POSTHOG_AUTH_HEADER": "Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
}
}
}
}
Using EU cloud or self-hosted instances
If you're using PostHog EU cloud or a self-hosted instance, you can specify a custom base URL by adding the POSTHOG_BASE_URL environment variable when running the MCP server locally or on your own infrastructure, e.g. POSTHOG_BASE_URL=https://eu.posthog.com
Here are some examples of prompts you can use:
- What feature flags do I have active?
- Add a new feature flag for our homepage redesign
- What are my most common errors?
Development
To run the MCP server locally, run the following command:
pnpm run dev
And replace https://mcp.posthog.com/sse with http://localhost:8787/sse in the MCP configuration.
Project Structure
This repository is organized to support multiple language implementations:
typescript/- TypeScript implementation (current)python/- Python implementation (planned)schema/- Shared schema files generated from TypeScript for cross-language compatibility
Development Commands
pnpm run dev- Start development serverpnpm run schema:build:json- Generate JSON schema for other language implementationspnpm run lint:fix- Format and lint code
Environment variables
- Create
.dev.varsin the root - Add Inkeep API key to enable
docs-searchtool (seeInkeep API key - mcp)
INKEEP_API_KEY="..."
Configuring the Model Context Protocol Inspector
During development you can directly inspect the MCP tool call results using the MCP Inspector.
You can run it using the following command:
npx @modelcontextprotocol/inspector npx -y mcp-remote@latest http://localhost:8787/sse --header "\"Authorization: Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}\""
Alternatively, you can use the following configuration in the MCP Inspector:
Use transport type STDIO.
Command:
npx
Arguments:
-y mcp-remote@latest http://localhost:8787/sse --header "Authorization: Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.