# How to integrate Graphhopper MCP with Autogen ```json { "title": "How to integrate Graphhopper MCP with Autogen", "toolkit": "Graphhopper", "toolkit_slug": "graphhopper", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/graphhopper/framework/autogen", "markdown_url": "https://composio.dev/toolkits/graphhopper/framework/autogen.md", "updated_at": "2026-05-06T08:14:45.265Z" } ``` ## Introduction This guide walks you through connecting Graphhopper to AutoGen using the Composio tool router. By the end, you'll have a working Graphhopper agent that can optimize delivery routes for multiple trucks, find all areas reachable within 15 minutes, convert a list of addresses to coordinates through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Graphhopper account through Composio's Graphhopper MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Graphhopper with - [OpenAI Agents SDK](https://composio.dev/toolkits/graphhopper/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/graphhopper/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/graphhopper/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/graphhopper/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/graphhopper/framework/codex) - [OpenClaw](https://composio.dev/toolkits/graphhopper/framework/openclaw) - [Hermes](https://composio.dev/toolkits/graphhopper/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/graphhopper/framework/cli) - [Google ADK](https://composio.dev/toolkits/graphhopper/framework/google-adk) - [LangChain](https://composio.dev/toolkits/graphhopper/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/graphhopper/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/graphhopper/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/graphhopper/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/graphhopper/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 Graphhopper - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Graphhopper tools - Run a live chat loop where you ask the agent to perform Graphhopper 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 Graphhopper MCP server, and what's possible with it? The Graphhopper MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Graphhopper account. It provides structured and secure access to powerful routing, geocoding, and optimization services, so your agent can perform actions like planning routes, solving vehicle routing problems, geocoding addresses, and generating travel time isochrones on your behalf. - Advanced route planning and optimization: Calculate complex routes for cars, bikes, or trucks using advanced parameters, waypoints, and custom profiles, all without manual map work. - Batch distance and time calculations: Let your agent generate distance or time matrices for multiple origins and destinations, streamlining logistics and route optimization tasks. - Geocoding and reverse geocoding: Convert between street addresses and GPS coordinates, or look up locations by latitude/longitude, making address management and mapping effortless. - Isochrone map generation: Automatically create isochrone polygons to visualize areas reachable within a specific travel time or distance from any point—perfect for delivery zones, emergency planning, or site selection. - Vehicle routing problem (VRP) solving: Offload complex fleet and logistics challenges to your agent, letting it assign deliveries, optimize routes, and minimize travel distances or costs using Graphhopper's VRP tools. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `GRAPHHOPPER_CLUSTER_POST` | Capacity Clustering | Tool to solve capacity clustering problem. Use when assigning a set of customers to clusters to minimize total distance synchronously. | | `GRAPHHOPPER_GEOCODE_GET` | GraphHopper Geocoding | Tool to perform forward or reverse geocoding. Use when converting between textual addresses and latitude/longitude coordinates. | | `GRAPHHOPPER_ISOCHRONE_GET` | Get Isochrone | Tool to compute isochrone polygons for a given point. Use when you need to determine areas reachable within time or distance constraints. | | `GRAPHHOPPER_MATRIX_POST` | Calculate Matrix | Tool to calculate distance, time, or weight matrices via POST. Use when you have multiple origins/destinations or a symmetric point set and need a single batch request. | | `GRAPHHOPPER_PROFILES_GET` | Get Custom Profiles | Tool to retrieve a list of all user-defined routing profiles. Use when you need to list custom profiles. | | `GRAPHHOPPER_ROUTE_POST` | POST Route | Tool to calculate complex routes via POST /route. Use when you need advanced route planning with custom parameters. | | `GRAPHHOPPER_UPLOAD_GPX_FILE` | Upload GPX File | Tool to upload a GPX file to a public file hosting endpoint. Returns a public URL which can be used where a 's3key' is required. | | `GRAPHHOPPER_VRP_POST` | GraphHopper VRP POST | Tool to initiate VRP optimization. Use when you need to solve vehicle routing problems synchronously. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Graphhopper MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Graphhopper. Instead of manually wiring Graphhopper 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 Graphhopper 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 Graphhopper 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 Graphhopper 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 Graphhopper 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 Graphhopper session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["graphhopper"] ) 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 Graphhopper 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 Graphhopper assistant agent with MCP tools agent = AssistantAgent( name="graphhopper_assistant", description="An AI assistant that helps with Graphhopper 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 Graphhopper 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 Graphhopper 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 Graphhopper session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["graphhopper"] ) 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 Graphhopper assistant agent with MCP tools agent = AssistantAgent( name="graphhopper_assistant", description="An AI assistant that helps with Graphhopper 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 Graphhopper 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 Graphhopper 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 Graphhopper, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Graphhopper MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/graphhopper/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/graphhopper/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/graphhopper/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/graphhopper/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/graphhopper/framework/codex) - [OpenClaw](https://composio.dev/toolkits/graphhopper/framework/openclaw) - [Hermes](https://composio.dev/toolkits/graphhopper/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/graphhopper/framework/cli) - [Google ADK](https://composio.dev/toolkits/graphhopper/framework/google-adk) - [LangChain](https://composio.dev/toolkits/graphhopper/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/graphhopper/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/graphhopper/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/graphhopper/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/graphhopper/framework/crew-ai) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. 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However, with the Composio Tool Router, agents can dynamically load tools from Graphhopper 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 Graphhopper tools. ### Can I manage the permissions and scopes for Graphhopper while using Tool Router? Yes, absolutely. You can configure which Graphhopper 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 Graphhopper data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)