How to integrate Here MCP with LangChain

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Introduction

This guide walks you through connecting Here to LangChain 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 LangChain 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
  • Connect your Here project to Composio
  • Create a Tool Router MCP session for Here
  • Initialize an MCP client and retrieve Here tools
  • Build a LangChain agent that can interact with Here
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Here functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Here tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Here
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['here']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Here tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Here tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "here-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Here MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Here tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Here related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['here']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "here-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Here related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Here through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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

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 LangChain?

Yes, you can. LangChain 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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