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How to integrate Mapbox MCP with Autogen

Connect Autogen to Mapbox MCP. Batch geocode these 10 addresses, get directions from times square to jfk, and more using natural language, with authentication handled for you.

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Mapbox is a platform providing powerful maps, navigation, and location services for developers. Integrate Mapbox for dynamic, interactive mapping and geospatial insights in your apps.

32 Tools

Introduction

This guide walks you through connecting Mapbox to AutoGen using the Composio tool router. By the end, you'll have a working Mapbox agent that can geocode and reverse geocode addresses, get directions, build isochrones, search places by category, and render static map images through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Mapbox account through Composio's Mapbox MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Mapbox with

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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 Mapbox
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Mapbox tools
  • Run a live chat loop where you ask the agent to perform Mapbox 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 Mapbox MCP server, and what's possible with it?

The Mapbox MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mapbox account. It provides structured and secure access to your mapping and location data, so your agent can perform actions like geocoding addresses, calculating travel routes, retrieving map embeds, and analyzing travel matrices on your behalf.

  • Batch and individual geocoding: Instantly convert addresses or place names to geographic coordinates—or reverse geocode coordinates to place names—using both batch and individual tools.
  • Route and directions retrieval: Let your agent fetch optimized driving, walking, or cycling directions between waypoints, including turn-by-turn instructions when needed.
  • Distance and travel time analysis: Have the agent generate travel time and distance matrices to compare routes or plan logistics across multiple locations.
  • Map style embed generation: Retrieve ready-to-use embeddable HTML for your custom Mapbox map styles, perfect for sharing or displaying maps in web apps.
  • Permanent geocoding and font data retrieval: Access enterprise-grade, cacheable geocoding data or fetch font glyph ranges for custom rendering and advanced mapping use cases.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Mapbox account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Mapbox via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 Mapbox connections to use
5

Import dependencies and create Tool Router session

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 Mapbox session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["mapbox"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Mapbox tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

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")}
)

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
7

Create the model client and agent

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 Mapbox assistant agent with MCP tools
    agent = AssistantAgent(
        name="mapbox_assistant",
        description="An AI assistant that helps with Mapbox operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Mapbox tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Mapbox 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Mapbox 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

Complete Code

Here's the complete code to get you started with Mapbox and AutoGen:

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 Mapbox session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["mapbox"]
    )
    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 Mapbox assistant agent with MCP tools
        agent = AssistantAgent(
            name="mapbox_assistant",
            description="An AI assistant that helps with Mapbox 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 Mapbox 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 Mapbox 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 Mapbox, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Mapbox action and event your agent gets out of the box.

Batch Geocode V6

Tool to perform batch geocoding with up to 1000 queries in a single request.

Forward Geocode V5

Tool to search for places by name or address using Mapbox Geocoding v5 API (forward geocoding).

Batch Geocoding

Tool to perform batch forward or reverse geocoding for multiple locations.

Forward Geocoding

Tool to convert free-form or structured address into geographic coordinates and place features.

Permanent Forward Geocoding

Tool to perform permanent forward geocoding.

Permanent Reverse Geocoding

Reverse geocode coordinates through Mapbox's permanent geocoding endpoint to obtain cacheable place data.

Reverse Geocoding

Tool to reverse geocode coordinates into place names.

Get Access Token

Extract a Mapbox access token from connection metadata and check its format for downstream use.

Get Isochrone

Tool to calculate areas reachable within a specified amount of time or distance from a location.

Get Map Matching

Tool to snap fuzzy GPS traces to roads on the road network.

Get Optimization V1

Calculate optimized trips visiting a set of waypoints using driving, traffic-aware driving, walking, or cycling profiles.

Get Sprite

Tool to retrieve a sprite image or its JSON document from a Mapbox style.

Get Static Image

Request a static map image from a Mapbox Studio style.

Get Static Tiles

Tool to retrieve raster tiles from a Mapbox Studio style.

Get Token Information

Tool to retrieve information about a Mapbox access token and validate its status.

Get Vector Tiles

Tool to retrieve vector tiles from Mapbox-hosted vector tilesets.

Map Matching (POST)

Tool to snap GPS coordinates to the road network using POST method for longer coordinate lists.

Query Tile Features

Tool to retrieve data about specific features from vector tilesets based on a location.

Request Style Embed HTML

Retrieve embeddable HTML for a Mapbox style that can be embedded in an iframe.

Retrieve Directions

Retrieve directions between waypoints, with optional turn-by-turn instructions.

Retrieve Font Glyph Ranges

Tool to retrieve font glyph ranges as PBF tiles.

Retrieve Marker

Tool to retrieve a standalone marker image without any background map.

Retrieve Matrix

Retrieve a travel time and/or distance matrix between multiple locations.

Retrieve Searchbox Place Details

Tool to retrieve full details for a specific place by its Mapbox ID.

Retrieve Style

Retrieve a Mapbox style's details, including its layers, sources, sprite URL, and glyph URL, for inspecting or analyzing map configurations.

Retrieve Style WMTS

Retrieve a WMTS (Web Map Tile Service) capabilities document for a Mapbox style.

Retrieve Tileset Metadata

Tool to retrieve metadata for a Mapbox tileset.

Reverse Geocoding V6

Tool to convert geographic coordinates to place names using Geocoding v6 API.

Search Box Reverse Geocoding

Tool to convert coordinates to places using the Search Box API (reverse geocoding).

Search Box Forward

Tool to search for places by name or address using the Search Box API.

Search by Category

Tool to search for places by category (e.

Search Box Suggest

Tool to get autocomplete suggestions for a partial search query.

FRAMEWORKS

How to build Mapbox MCP Agent with another framework

Claude Code logo

Claude Code

Use Mapbox MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Mapbox MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Mapbox MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Mapbox MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Mapbox MCP with Grok Bot

Codex logo

Codex

Use Mapbox MCP with Codex

OpenClaw logo

OpenClaw

Use Mapbox MCP with OpenClaw

Hermes logo

Hermes

Use Mapbox MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Mapbox MCP with Atomic Agent

Google ADK logo

Google ADK

Use Mapbox MCP with Google ADK

LangChain logo

LangChain

Use Mapbox MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Mapbox MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Mapbox MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Mapbox MCP with LlamaIndex

CrewAI logo

CrewAI

Use Mapbox MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Mapbox MCP with Pydantic AI

FAQ

Frequently asked questions

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

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 Mapbox tools.

Yes, absolutely. You can configure which Mapbox 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.

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 Mapbox data and credentials are handled as safely as possible.

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