How to integrate Here MCP with Autogen

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Introduction

This guide walks you through connecting Here to AutoGen using the Composio tool router. By the end, you'll have a working Here agent that can find coffee shops near central park, get driving route for delivery truck, convert address to latitude and longitude, show hybrid map tile for times square through natural language commands.

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

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

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

The Here MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Here account. It provides structured and secure access to powerful location, mapping, and geocoding services, so your agent can perform actions like searching places, calculating routes, fetching map imagery, and converting addresses or coordinates on your behalf.

  • Smart place discovery and suggestions: Ask your agent to find points of interest, get autosuggested places based on partial queries, or discover addresses near a location.
  • Geocoding and reverse geocoding: Convert addresses to geographic coordinates or vice versa, enabling seamless location lookup and mapping in your workflows.
  • Map tile and imagery retrieval: Direct your agent to fetch satellite, base, or hybrid map tiles for specific locations, zoom levels, and formats for rich visual context.
  • Advanced routing and fleet planning: Have your agent calculate optimized routes with vehicle profiles, constraints, and even isolines for reachable areas based on time or distance.
  • Nearby search and contextual browsing: Let your agent browse or search for places around a given location, filtered by categories or names, to surface relevant local information.

Supported Tools & Triggers

Tools
Autosuggest PlacesTool to fetch possible completions for a partial search term.
Browse PlacesTool to search for places around a given location with optional filters.
Calculate Fleet Telematics RouteTool to calculate a route between waypoints with vehicle profile options.
Coordinates to Tile IndicesTool to convert geographic coordinates to Web Mercator XYZ tile indices.
Discover PlacesTool to discover places and addresses by free-form text near a location.
Geocode AddressTool to convert structured address data into geographic coordinates.
Get Aerial TileTool to retrieve a satellite/aerial map tile.
Get Base Map TileTool to retrieve a base map tile image without labels.
Get Hybrid Map TileTool to retrieve a hybrid (aerial + labels) map tile.
Get IsolinesTool to calculate isolines.
Get Label TileTool to retrieve a label overlay tile.
Get Line Overlay TileTool to retrieve a line overlay tile.
Get Map ImageTool to retrieve a static map image.
Get Base Map TileTool to retrieve a base map tile.
Compute Routing MatrixTool to compute a routing distance/time matrix.
Get Meta Info TileTool to retrieve metadata for a specific map tile.
Get POI TileTool to retrieve a point-of-interest overlay tile.
Get Terrain Map TileTool to retrieve a terrain map tile image.
Get Traffic FlowTool to retrieve real-time traffic flow data.
Get Traffic IncidentsTool to fetch real-time traffic incidents within a specified area.
Get Traffic TileTool to retrieve a traffic overlay tile.
Get Waypoint SequenceTool to optimize the visit order of multiple waypoints.
Daily Weather ForecastTool to provide daily weather forecasts (up to 7 days).
Get Weather ObservationTool to retrieve current weather observation.
Hourly Weather ForecastTool to fetch hourly weather forecasts.
Lookup Place DetailsTool to look up detailed information for a place by its HERE ID.
Reverse Geocode CoordinatesTool to convert geographic coordinates into a human-readable address.
Weather AlertsTool to retrieve severe weather alerts for specified locations or routes.
Get Astronomy ForecastTool to fetch astronomical data (sunrise, sunset) for a specific location.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

You will need:

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

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.

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 Here via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

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 Here connections to use

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 Here session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["here"]
    )
    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 Here tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

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

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 Here assistant agent with MCP tools
    agent = AssistantAgent(
        name="here_assistant",
        description="An AI assistant that helps with Here 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 Here tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Here 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 Here 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 Here 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 Here session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["here"]
    )
    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 Here assistant agent with MCP tools
        agent = AssistantAgent(
            name="here_assistant",
            description="An AI assistant that helps with Here 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 Here 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 Here 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 Here, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Here MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Here MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Here MCP with Claude Agent SDK

Google ADK

Google ADK

Use Here MCP with Google ADK

LangChain

LangChain

Use Here MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Here MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Here MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Here MCP with LlamaIndex

CrewAI

CrewAI

Use Here MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Here MCP?

With a standalone Here MCP server, the agents and LLMs can only access a fixed set of Here tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Here 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 Here tools.

Can I manage the permissions and scopes for Here while using Tool Router?

Yes, absolutely. You can configure which Here 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 Here data and credentials are handled as safely as possible.

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