# How to integrate Simple analytics MCP with Autogen

```json
{
  "title": "How to integrate Simple analytics MCP with Autogen",
  "toolkit": "Simple analytics",
  "toolkit_slug": "simple_analytics",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/simple_analytics/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/simple_analytics/framework/autogen.md",
  "updated_at": "2026-05-12T10:26:20.565Z"
}
```

## Introduction

This guide walks you through connecting Simple analytics to AutoGen using the Composio tool router. By the end, you'll have a working Simple analytics agent that can show visitor stats for your main website, export last month's raw traffic data, list all websites linked to your account through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Simple analytics account through Composio's Simple analytics MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Simple analytics with

- [OpenAI Agents SDK](https://composio.dev/toolkits/simple_analytics/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/simple_analytics/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/simple_analytics/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/simple_analytics/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/simple_analytics/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/simple_analytics/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/simple_analytics/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/simple_analytics/framework/cli)
- [Google ADK](https://composio.dev/toolkits/simple_analytics/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/simple_analytics/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/simple_analytics/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/simple_analytics/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/simple_analytics/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/simple_analytics/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Simple analytics
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Simple analytics tools
- Run a live chat loop where you ask the agent to perform Simple analytics operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

## What is the Simple analytics MCP server, and what's possible with it?

The Simple analytics MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Simple Analytics account. It provides structured and secure access to privacy-friendly analytics data, so your agent can perform actions like retrieving website stats, exporting raw data, and listing all your tracked websites with ease.
- List all connected websites: Quickly get a comprehensive list of all websites associated with your Simple Analytics account, making it easy for your agent to select and manage different sites.
- Export raw analytics data: Direct your agent to export detailed raw data points—like page views and events—for any website, ready for custom analysis or sharing in CSV or JSON formats.
- Retrieve key website metrics: Ask your agent to fetch aggregated statistics for a specific site, including visitors, pageviews, bounce rate, and other essential metrics in one go.
- Automated traffic reporting: Let your agent generate periodic or on-demand traffic reports, summarizing recent performance trends across your sites.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SIMPLE_ANALYTICS_ADMIN_API_LIST_WEBSITES` | List Websites (Admin API) | Tool to list all websites associated with the authenticated user. Use after authenticating an admin account to retrieve website list. |
| `SIMPLE_ANALYTICS_EXPORT_API_GET_RAW_DATA` | Export Raw Data Points | Tool to export raw data points (page views and events) for a specific website. Use when you need to download CSV or JSON exports of site traffic. |
| `SIMPLE_ANALYTICS_GET_AGGREGATED_STATS` | Get aggregated website stats | Tool to retrieve aggregated statistics for a specified website. Use when you need an overview of key metrics like visitors, pageviews, bounce rate, and more. |
| `SIMPLE_ANALYTICS_SEND_EVENT` | Send Server-Side Event | Tool to submit server-side events or pageviews to Simple Analytics. Use for mobile apps, backend tracking, or scenarios where JavaScript is not available. Supports custom metadata for enriched event data. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Simple analytics MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Simple analytics. Instead of manually wiring Simple analytics APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Simple analytics account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Simple analytics via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Simple analytics connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Simple analytics tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Simple analytics session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["simple_analytics"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Simple analytics tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Simple analytics assistant agent with MCP tools
    agent = AssistantAgent(
        name="simple_analytics_assistant",
        description="An AI assistant that helps with Simple analytics operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Simple analytics tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Simple analytics related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Simple analytics session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["simple_analytics"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Simple analytics assistant agent with MCP tools
        agent = AssistantAgent(
            name="simple_analytics_assistant",
            description="An AI assistant that helps with Simple analytics operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Simple analytics related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Simple analytics through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Simple analytics, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Simple analytics MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/simple_analytics/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/simple_analytics/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/simple_analytics/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/simple_analytics/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/simple_analytics/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/simple_analytics/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/simple_analytics/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/simple_analytics/framework/cli)
- [Google ADK](https://composio.dev/toolkits/simple_analytics/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/simple_analytics/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/simple_analytics/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/simple_analytics/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/simple_analytics/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/simple_analytics/framework/crew-ai)

## Related Toolkits

- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.
- [Bright Data MCP](https://composio.dev/toolkits/brightdata_mcp) - Bright Data MCP is an AI-powered web scraping and data collection platform. Instantly access public web data in real time with advanced scraping tools.
- [Browseai](https://composio.dev/toolkits/browseai) - Browseai is a web automation and data extraction platform that turns any website into an API. It's perfect for monitoring websites and retrieving structured data without manual scraping.
- [ClickHouse](https://composio.dev/toolkits/clickhouse) - ClickHouse is an open-source, column-oriented database for real-time analytics and big data processing using SQL. Its lightning-fast query performance makes it ideal for handling large datasets and delivering instant insights.
- [Coinmarketcal](https://composio.dev/toolkits/coinmarketcal) - CoinMarketCal is a community-powered crypto calendar for upcoming events, announcements, and releases. It helps traders track market-moving developments and stay ahead in the crypto space.
- [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks.
- [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights.
- [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently.
- [Datagma](https://composio.dev/toolkits/datagma) - Datagma delivers data intelligence and analytics for business growth and market discovery. Get actionable market insights and track competitors to inform your strategy.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Dovetail](https://composio.dev/toolkits/dovetail) - Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries.
- [Dub](https://composio.dev/toolkits/dub) - Dub is a short link management platform with analytics and API access. Use it to easily create, manage, and track branded short links for your business.
- [Fireflies](https://composio.dev/toolkits/fireflies) - Fireflies.ai is an AI-powered meeting assistant that records, transcribes, and analyzes voice conversations. It helps teams capture call notes automatically and search or summarize meetings effortlessly.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Simple analytics MCP?

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

### Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen 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 Simple analytics tools.

### Can I manage the permissions and scopes for Simple analytics while using Tool Router?

Yes, absolutely. You can configure which Simple analytics 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 Simple analytics data and credentials are handled as safely as possible.

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