# How to integrate Graphhopper MCP with CrewAI ```json { "title": "How to integrate Graphhopper MCP with CrewAI", "toolkit": "Graphhopper", "toolkit_slug": "graphhopper", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/graphhopper/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/graphhopper/framework/crew-ai.md", "updated_at": "2026-05-06T08:14:45.265Z" } ``` ## Introduction This guide walks you through connecting Graphhopper to CrewAI 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 CrewAI 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) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Graphhopper connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Graphhopper - Build a conversational loop where your agent can execute Graphhopper operations ## What is CrewAI? CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews. Key features include: - Agent Roles: Define specialized agents with specific goals and backstories - Task Management: Create tasks with clear descriptions and expected outputs - Crew Orchestration: Combine agents and tasks into collaborative workflows - MCP Integration: Connect to external tools through Model Context Protocol ## 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 agent to Graphhopper. It provides structured and secure access so your agent can perform Graphhopper operations on your behalf through a secure, permission-based interface. 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 Before starting, make sure you have: - Python 3.9 or higher - A Composio account and API key - A Graphhopper connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 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 **What's happening:** - composio connects your agent to Graphhopper via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates with Composio - USER_ID scopes the session to your account - OPENAI_API_KEY lets CrewAI use your chosen OpenAI model ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **What's happening:** - CrewAI classes define agents and tasks, and run the workflow - MCPServerHTTP connects the agent to an MCP endpoint - Composio will give you a short lived Graphhopper MCP URL ```python import os from composio import Composio from crewai import Agent, Task, Crew from crewai_tools import MCPServerAdapter import dotenv dotenv.load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") ``` ### 5. Create a Composio Tool Router session for Graphhopper **What's happening:** - You create a Graphhopper only session through Composio - Composio returns an MCP HTTP URL that exposes Graphhopper tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["graphhopper"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **What's Happening:** - Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication. - MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format. - Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools. - Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops. - Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries. ```python server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users search the internet effectively", backstory="You are a helpful assistant with access to search tools.", tools=tools, verbose=False, max_iter=10, ) ``` ### 7. Create a CLI Chatloop and define the Crew **What's Happening:** - Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable. - Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean. - Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses. - Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context. - Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response. - Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity. ```python print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Complete Code ```python from crewai import Agent, Task, Crew, LLM from crewai_tools import MCPServerAdapter from composio import Composio from dotenv import load_dotenv import os load_dotenv() GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not GOOGLE_API_KEY: raise ValueError("GOOGLE_API_KEY is not set in the environment.") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment.") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment.") # Initialize Composio and create a session composio = Composio(api_key=COMPOSIO_API_KEY) session = composio.create( user_id=COMPOSIO_USER_ID, toolkits=["graphhopper"], ) url = session.mcp.url # Configure LLM llm = LLM( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY"), ) server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users with internet searches", backstory="You are an expert assistant with access to Composio Search tools.", tools=tools, llm=llm, verbose=False, max_iter=10, ) print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Conclusion You now have a CrewAI agent connected to Graphhopper through Composio's Tool Router. The agent can perform Graphhopper operations through natural language commands. Next steps: - Add role-specific instructions to customize agent behavior - Plug in more toolkits for multi-app workflows - Chain tasks for complex multi-step operations ## 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) ## 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. It helps you build flexible automations with complex conditions, schedules, and integrations. - [Basin](https://composio.dev/toolkits/basin) - Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code. - [Bouncer](https://composio.dev/toolkits/bouncer) - Bouncer is an email validation platform that verifies the authenticity of email addresses in real-time and batch. It helps boost deliverability and reduce bounce rates for your communications. - [Conveyor](https://composio.dev/toolkits/conveyor) - Conveyor is a platform that automates security reviews with a Trust Center and AI-driven questionnaire automation. It streamlines compliance and vendor security processes for faster, hassle-free reviews. - [Crowdin](https://composio.dev/toolkits/crowdin) - Crowdin is a localization management platform that streamlines translation workflows and collaboration. 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Capture, manage, and integrate form responses securely for streamlined workflows. - [Hyperbrowser](https://composio.dev/toolkits/hyperbrowser) - Hyperbrowser is a next-generation platform for scalable browser automation. It empowers AI agents to interact with web apps, automate workflows, and handle browser sessions at scale. - [La Growth Machine](https://composio.dev/toolkits/lagrowthmachine) - La Growth Machine automates multi-channel sales outreach and routine tasks for sales teams. Streamline your workflow and focus on closing more deals. - [Leverly](https://composio.dev/toolkits/leverly) - Leverly is a workflow automation platform that connects and coordinates actions across your apps. It streamlines repetitive processes so your business runs smoother, faster, and with fewer manual steps. - [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination. - [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code. - [Ntfy](https://composio.dev/toolkits/ntfy) - Ntfy is a notification service to send push messages to phones or desktops. Instantly deliver alerts and updates to users, devices, or teams. - [Persona](https://composio.dev/toolkits/persona) - Persona offers identity infrastructure to automate user verification and compliance. It helps organizations securely verify users and reduce fraud risk. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Graphhopper MCP? With a standalone Graphhopper MCP server, the agents and LLMs can only access a fixed set of Graphhopper tools tied to that server. 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 CrewAI? Yes, you can. CrewAI 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)