# How to integrate Felt MCP with Autogen ```json { "title": "How to integrate Felt MCP with Autogen", "toolkit": "Felt", "toolkit_slug": "felt", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/felt/framework/autogen", "markdown_url": "https://composio.dev/toolkits/felt/framework/autogen.md", "updated_at": "2026-05-12T10:11:13.566Z" } ``` ## Introduction This guide walks you through connecting Felt to AutoGen using the Composio tool router. By the end, you'll have a working Felt agent that can add geojson features to an existing map, duplicate a project map for a new client, delete a layer from your city zoning map through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Felt account through Composio's Felt MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Felt with - [OpenAI Agents SDK](https://composio.dev/toolkits/felt/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/felt/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/felt/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/felt/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/felt/framework/codex) - [OpenClaw](https://composio.dev/toolkits/felt/framework/openclaw) - [Hermes](https://composio.dev/toolkits/felt/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/felt/framework/cli) - [Google ADK](https://composio.dev/toolkits/felt/framework/google-adk) - [LangChain](https://composio.dev/toolkits/felt/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/felt/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/felt/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/felt/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/felt/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 Felt - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Felt tools - Run a live chat loop where you ask the agent to perform Felt 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 Felt MCP server, and what's possible with it? The Felt MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Felt account. It provides structured and secure access to your maps, projects, and geospatial data, so your agent can perform actions like creating projects, modifying maps, updating map elements, and retrieving user or map details on your behalf. - Project and map creation: Instantly have your agent create new Felt projects and initialize interactive maps to kickstart geospatial workflows. - Element and layer management: Direct your agent to add, update, or delete map elements and layers—making it easy to modify map content or clean up unwanted data. - Map duplication and deletion: Clone existing maps for experimentation or backup, or remove entire maps and projects when they’re no longer needed. - Detailed map and user insights: Retrieve comprehensive details about any specific map or your authenticated user profile for streamlined map management and reporting. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `FELT_CREATE_OR_UPDATE_ELEMENTS` | Create or Update Elements | Create or update map elements using GeoJSON FeatureCollection format. Creates new elements by default; to update existing elements, include 'felt:id' in the feature's properties. Supports Point, LineString, Polygon, and Multi-type geometries. Returns the created/updated elements with assigned IDs and Felt-specific properties. | | `FELT_CREATE_PROJECT` | Create Project | Create a new Felt project with the specified name and visibility settings. Projects are organizational containers for grouping related maps within a workspace. | | `FELT_DELETE_ELEMENT` | Delete Element | Tool to delete a specific element from a map. Use when you have both map and element IDs and need to remove the element permanently. | | `FELT_DELETE_LAYER` | Delete Layer | Tool to delete a specific layer from a map. Use when you have the map's and layer's IDs and need to remove it permanently. | | `FELT_DELETE_MAP` | Delete Map | Permanently deletes a map and all its associated data from Felt. WARNING: This action cannot be undone. The map and all its layers, elements, and comments will be permanently removed. Use when you have the map's ID and need to permanently remove it. Returns no content (HTTP 204) on success. | | `FELT_DELETE_PROJECT` | Delete Project | Tool to delete a project and all its contents. Use when you need to permanently remove a project after confirmation. | | `FELT_DUPLICATE_MAP` | Duplicate Map | Creates a complete copy of a Felt map including all layers, elements, and configuration. Use when you need to clone an existing map to a new location or create a template-based map. The duplicated map can optionally be placed in a specific project or folder. | | `FELT_GET_MAP_DETAILS` | Get Map Details | Retrieves comprehensive details of a specific Felt map including title, URL, layers, elements, basemap settings, access permissions, and timestamps. Requires a valid map ID. Use this when you need to: - Get complete map configuration and metadata - Access map layers and elements - Check map permissions and access settings - Retrieve map URLs for sharing | | `FELT_GET_USER_DETAILS` | Get User Details | Tool to retrieve information about the authenticated user. Use after obtaining a valid token to fetch user profile details. | | `FELT_LIST_ELEMENT_GROUPS` | List Element Groups | Retrieves all element groups from a Felt map. Element groups are collections of geographic features (points, lines, polygons) organized together. Each group returns a GeoJSON FeatureCollection with the group's elements, along with styling properties like color and symbol. Use this when you need to discover what element groups exist on a map or access grouped geographic data. | | `FELT_LIST_ELEMENTS` | List Elements | Lists all elements on a specific map as a GeoJSON FeatureCollection. Returns elements that are not in element groups. Use when you need to retrieve the map's direct elements after obtaining a valid map_id. | | `FELT_LIST_LAYERS` | List Layers | Tool to list all layers on a specific map. Returns all layers present on the map with their complete metadata including status, geometry type, styling, and attributes. Use this when you need to inspect or enumerate the data layers on a map. | | `FELT_LIST_PROJECTS` | List Projects | Tool to retrieve a list of projects accessible to the user. Use when you need to browse or select from existing projects before proceeding. | | `FELT_LIST_SOURCES` | List Sources | List all data sources (external data connections) accessible to the authenticated user. Sources represent connections to external data providers like BigQuery, PostgreSQL, S3, Snowflake, etc. Use this to discover available sources before importing data from them into Felt maps. Each source includes sync status, connection type, and access permissions. | | `FELT_UPDATE_PROJECT` | Update Project | Tool to update an existing project's name or visibility. Use after confirming the project_id. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Felt MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Felt. Instead of manually wiring Felt 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 Felt 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 Felt 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 Felt 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 Felt 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 Felt session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["felt"] ) 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 Felt 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 Felt assistant agent with MCP tools agent = AssistantAgent( name="felt_assistant", description="An AI assistant that helps with Felt 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 Felt 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 Felt 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 Felt session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["felt"] ) 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 Felt assistant agent with MCP tools agent = AssistantAgent( name="felt_assistant", description="An AI assistant that helps with Felt 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 Felt 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 Felt 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 Felt, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Felt MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/felt/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/felt/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/felt/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/felt/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/felt/framework/codex) - [OpenClaw](https://composio.dev/toolkits/felt/framework/openclaw) - [Hermes](https://composio.dev/toolkits/felt/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/felt/framework/cli) - [Google ADK](https://composio.dev/toolkits/felt/framework/google-adk) - [LangChain](https://composio.dev/toolkits/felt/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/felt/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/felt/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/felt/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/felt/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 detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. 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Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. 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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Felt MCP? With a standalone Felt MCP server, the agents and LLMs can only access a fixed set of Felt tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Felt 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 Felt tools. ### Can I manage the permissions and scopes for Felt while using Tool Router? Yes, absolutely. You can configure which Felt 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 Felt data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)