How to integrate Mixpanel MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Mixpanel to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Mixpanel agent that can show daily active users for last month, list top events by user engagement, analyze conversion funnel for signup flow through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Mixpanel account through Composio's Mixpanel MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Mixpanel
  • Configure an AI agent that can use Mixpanel as a tool
  • Run a live chat session where you can ask the agent to perform Mixpanel operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Mixpanel MCP server, and what's possible with it?

The Mixpanel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mixpanel account. It provides structured and secure access to your product analytics data, so your agent can perform actions like retrieving event metrics, analyzing cohorts, exploring funnels, and running custom queries on your behalf.

  • Event property and trend analysis: Ask your agent to fetch unique, total, or average values for specific events and properties over time to spot trends and measure engagement.
  • Cohort and funnel exploration: Have your agent pull lists of saved cohorts or funnels, or retrieve detailed funnel performance data to understand user journeys.
  • User activity and frequency reporting: Direct your agent to analyze how frequently users perform key events or to get event activity feeds for individual profiles.
  • Custom JQL query execution: Run advanced, custom JavaScript queries through your agent for deep, flexible analytics tailored to your business questions.
  • Project and configuration management: Let your agent list all Mixpanel projects under your account, giving you quick access to metadata and configuration details.

Supported Tools & Triggers

Tools
Get Aggregated Event Property ValuesGet unique, total, or average data for a single event and property over days, weeks, or months.
Get Aggregate Event CountsGet aggregate event counts over time.
Get Aggregate EventsGet aggregate event counts over time.
Get All ProjectsGet all projects associated with the authenticated mixpanel account.
Execute JQL QueryExecute a custom jql (javascript query language) query against mixpanel's query api.
List Saved CohortsGet list of all cohorts in a mixpanel project.
List Saved FunnelsGet the names and funnel ids of your funnels.
Get Profile Event ActivityGet event activity feed for specified users from mixpanel query api.
Query Frequency ReportGet data about how frequently users are performing events.
Query Saved FunnelGet data for a funnel.
Query Saved InsightGet data from your insights reports.
Query Numeric Average ReportAverages an expression for events per unit time.
Query Numeric Segmentation ReportGet data for an event, segmented and filtered by properties, with values placed into numeric buckets.
Query Numeric Sum ReportSums an expression for events per unit time.
Query ProfilesQuery user or group profile data from mixpanel.
Query Retention ReportGet cohort analysis data.
Query Segmentation ReportGet data for an event, segmented and filtered by properties.
Get Today's Top EventsGet the top events for today, with their counts and the normalized percent change from yesterday.
Get Top Event PropertiesGet the top property names for an event.
Get Top Event Property ValuesGet the top values for a property.
Get Top EventsGet a list of the most common events over the last 31 days.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Mixpanel project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Mixpanel.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Mixpanel Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["mixpanel"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only mixpanel.
  • The router checks the user's Mixpanel connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Mixpanel.
  • This approach keeps things lightweight and lets the agent request Mixpanel tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Mixpanel. "
        "Help users perform Mixpanel operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Mixpanel and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Mixpanel operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Mixpanel.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Mixpanel and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["mixpanel"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Mixpanel. "
        "Help users perform Mixpanel operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Mixpanel MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Mixpanel.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Mixpanel MCP Agent with another framework

Claude Agent SDK

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LangChain

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Mastra AI

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CrewAI

CrewAI

Use Mixpanel MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Mixpanel MCP?

With a standalone Mixpanel MCP server, the agents and LLMs can only access a fixed set of Mixpanel tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Mixpanel and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Mixpanel tools.

Can I manage the permissions and scopes for Mixpanel while using Tool Router?

Yes, absolutely. You can configure which Mixpanel scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Mixpanel data and credentials are handled as safely as possible.

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