Mixpanel

Connect AI agents to Mixpanel for advanced analytics and user behavior tracking

Prerequisites Before you begin, create an account and get your API Key.

Getting started

Connect to Mixpanel to track events, analyze user behavior, and generate insights from your product analytics through AI agents.

API

1. Install the SDKs (optional)

   pip

   pip install klavis
   
2. Create a Strata MCP Server with Mixpanel

   Python

   from klavis import Klavis
   from klavis.types import McpServerName
   
   klavis_client = Klavis(api_key="YOUR_API_KEY")
   
   # Create a Strata MCP server with Mixpanel
   response = klavis_client.mcp_server.create_strata_server(
       servers=[McpServerName.MIXPANEL],
       user_id="user123"
   )
   

   userId specifies whose connected accounts and data you are accessing in Klavis. It should be a unique id for yourself, your team, or your organization.

   API Reference

   Full Strata API endpoints

3. Authenticate with Service Account Credentials

   Python

   klavis_client.mcp_server.set_strata_auth(
       strata_id=response.strata_id,
       server_name=McpServerName.MIXPANEL,
       auth_data={
           "data": {
               "serviceaccount_username": "YOUR_MIXPANEL_SERVICE_ACCOUNT_USERNAME",
               "serviceaccount_secret": "YOUR_MIXPANEL_SERVICE_ACCOUNT_SECRET"
           }
       }
   )
   

   Get your Mixpanel service account credentials from your Mixpanel project settings. These credentials are required to access your analytics data.

   🎉 Your Mixpanel MCP Server is ready! Once authentication is complete, you can use your MCP server URL with any MCP-compatible client.

UI

1. Open Dashboard

   Go to your Dashboard.

2. Choose Mixpanel

   Select Mixpanel from the list of available integrations.

3. Authenticate

   Complete the authentication flow to connect your Mixpanel service account.

4. Use in your app

   Copy the MCP endpoint URL and add it to your MCP-supported client (Claude Desktop, Cursor, VS Code, etc.).

Open Source

1. Clone repository (for developers to build from source)

   git clone https://github.com/klavis-ai/klavis
   cd klavis/mcp_servers/mixpanel
   
2. Run with Docker

   # Pull the Docker image
   docker pull ghcr.io/klavis-ai/mixpanel-mcp-server:latest
   
   # Run with Mixpanel service account credentials
   docker run -p 5000:5000 \
     -e AUTH_DATA='{"data":{"serviceaccount_username":"your_username","serviceaccount_secret":"your_secret"}}' \
     ghcr.io/klavis-ai/mixpanel-mcp-server:latest
   
3. Configure MCP client

   {
     "mcpServers": {
       "mixpanel": {
         "url": "http://localhost:5000/mcp/"
       }
     }
   }
   

Available Tools

With our progressive discovery approach, Klavis System is capable of enabling all tools for Mixpanel. Please use the get_tools API for more details. If you find any tool that is missing, please reach out to [e-mail].

Next Steps

AI Platform Integrations

Integrate Klavis MCP Servers with leading AI platforms

Integrations

Explore available MCP servers

API Reference

REST endpoints and schemas

White-label Authentication

Customize OAuth flows with your own branding