# How to integrate Exist MCP with Autogen ```json { "title": "How to integrate Exist MCP with Autogen", "toolkit": "Exist", "toolkit_slug": "exist", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/exist/framework/autogen", "markdown_url": "https://composio.dev/toolkits/exist/framework/autogen.md", "updated_at": "2026-05-12T10:10:59.628Z" } ``` ## Introduction This guide walks you through connecting Exist to AutoGen using the Composio tool router. By the end, you'll have a working Exist agent that can show your top positive habits last month, list strongest correlations in your data, summarize your tracked mood this week through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Exist account through Composio's Exist MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Exist with - [OpenAI Agents SDK](https://composio.dev/toolkits/exist/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/exist/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/exist/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/exist/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/exist/framework/codex) - [OpenClaw](https://composio.dev/toolkits/exist/framework/openclaw) - [Hermes](https://composio.dev/toolkits/exist/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/exist/framework/cli) - [Google ADK](https://composio.dev/toolkits/exist/framework/google-adk) - [LangChain](https://composio.dev/toolkits/exist/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/exist/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/exist/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/exist/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/exist/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 Exist - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Exist tools - Run a live chat loop where you ask the agent to perform Exist 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 Exist MCP server, and what's possible with it? The Exist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Exist account. It provides structured and secure access to your personal analytics data, so your agent can perform actions like analyzing correlations, retrieving user attributes, exploring supported metrics, and inspecting your profile on your behalf. - Personal profile access and insights: Instantly retrieve and review your Exist user profile, including preferences and account settings, to keep your agent aware of your context. - Attribute exploration and discovery: Browse and list all available attribute templates or user attributes, making it easy to understand what metrics you can track, analyze, or visualize. - Correlation analysis: Ask your agent to fetch and explore recent correlations between tracked attributes—like how weather or sleep might relate to your mood or productivity. - Custom analytics setup: Let your agent help you discover and understand supported attribute templates before you start tracking or updating new data points. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `EXIST_ACQUIRE_ATTRIBUTE_OWNERSHIP` | Acquire Attribute Ownership | Tool to acquire ownership of attributes for the authenticated user. Allows your service to write data to these attributes. Use when you need to create or take ownership of attributes before writing data. Acquiring a templated attribute the user doesn't have yet will create this attribute and give you ownership. | | `EXIST_GET_ATTRIBUTES_WITH_VALUES` | Get Attributes With Values | Tool to retrieve attributes with their current values for the authenticated user. Use when you need both attribute metadata and their historical values. Results are limited to your read scopes. | | `EXIST_GET_ATTRIBUTE_TEMPLATES` | Get Attribute Templates | Tool to retrieve a paged list of supported attribute templates. Use when you need to browse available templates before creating or updating data. | | `EXIST_GET_AVERAGES` | Get Averages | Tool to retrieve the most recent average values for each tracked attribute, with one set per week. Returns overall weekly averages plus daily breakdowns (Monday-Sunday). Use include_historical flag to retrieve historical average records. | | `EXIST_GET_CORRELATIONS` | Get Correlations | Retrieve a paginated list of correlations discovered between tracked attributes in the last week. Correlations reveal statistical relationships between different metrics (e.g., sleep duration vs mood). Filter by relationship strength, confidence level (statistical significance), or specific attributes. Returns correlation coefficients, p-values, and human-readable descriptions. | | `EXIST_GET_INSIGHTS` | Get Insights | Tool to retrieve automatically-generated insights about patterns in tracked data for the authenticated user. Insights are observations about correlations, trends, and anomalies (e.g., "You walked more on days you slept well"). Use when analyzing user behavior patterns or displaying personalized feedback. | | `EXIST_GET_OWNED_ATTRIBUTES` | Get Owned Attributes | Tool to retrieve attributes owned by your service for the authenticated user. Use when you need to limit data updates to only the attributes your service controls. | | `EXIST_GET_USER_ATTRIBUTES` | Get User Attributes | Tool to retrieve a paged list of the user's attributes without values. Use when you need metadata on available attributes for filtering or selection. Omitting `groups` and `attributes` filters returns the full attribute catalog; use those filters to narrow results and avoid oversized responses. | | `EXIST_EXIST_GET_USER_PROFILE` | Get User Profile | Tool to retrieve the authenticated user's profile details and preferences. Use after authentication to inspect account settings and status. OAuth scopes granted during authentication determine which fields are returned; missing fields indicate insufficient scopes. Response includes a timezone field; use it when interpreting any date-based attributes. | | `EXIST_INCREMENT_ATTRIBUTE_VALUES` | Increment Attribute Values | Tool to increment attribute values by a delta amount rather than setting totals. Use for counters and cumulative data. Does not work with string, scale, or time of day attributes. | | `EXIST_EXIST_OAUTH2_AUTHORIZE` | Exist OAuth2 Authorize | Constructs an OAuth2 authorization URL for Exist.io. This tool generates the URL that users must visit in their browser to grant permissions to your application. After user consent, Exist redirects back to your redirect_uri with an authorization code that can be exchanged for an access token. This action does not make an API call - it only builds the authorization URL. | | `EXIST_RELEASE_ATTRIBUTE_OWNERSHIP` | Release Attribute Ownership | Tool to release ownership of attributes for the authenticated user. Use when your service will stop providing data for an attribute or becomes inactive. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Exist MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Exist. Instead of manually wiring Exist 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 Exist 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 Exist 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 Exist 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 Exist 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 Exist session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["exist"] ) 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 Exist 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 Exist assistant agent with MCP tools agent = AssistantAgent( name="exist_assistant", description="An AI assistant that helps with Exist 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 Exist 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 Exist 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 Exist session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["exist"] ) 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 Exist assistant agent with MCP tools agent = AssistantAgent( name="exist_assistant", description="An AI assistant that helps with Exist 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 Exist 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 Exist 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 Exist, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Exist MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/exist/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/exist/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/exist/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/exist/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/exist/framework/codex) - [OpenClaw](https://composio.dev/toolkits/exist/framework/openclaw) - [Hermes](https://composio.dev/toolkits/exist/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/exist/framework/cli) - [Google ADK](https://composio.dev/toolkits/exist/framework/google-adk) - [LangChain](https://composio.dev/toolkits/exist/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/exist/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/exist/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/exist/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/exist/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. - [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Exist MCP? With a standalone Exist MCP server, the agents and LLMs can only access a fixed set of Exist tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Exist 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 Exist tools. ### Can I manage the permissions and scopes for Exist while using Tool Router? Yes, absolutely. You can configure which Exist 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 Exist data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)