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How to integrate Geoapify MCP with LangChain

Connect LangChain to Geoapify MCP. Find latitude and longitude for an address, suggest address completions as i type, and more using natural language, with authentication handled for you.

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Geoapify is a comprehensive location-based services platform offering APIs for maps, geocoding, routing, and more. It enables developers to easily add powerful location capabilities and spatial intelligence to any application.

25 Tools

Introduction

This guide walks you through connecting Geoapify to LangChain using the Composio tool router. By the end, you'll have a working Geoapify agent that can geocode addresses, autocomplete locations, plan routes and travel matrices, search nearby places, and generate static map images through natural language commands.

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

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

Also integrate Geoapify with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotCodexOpenClawHermesAtomic AgentGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAIPydantic AIAutoGen

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Geoapify project to Composio
  • Create a Tool Router MCP session for Geoapify
  • Initialize an MCP client and retrieve Geoapify tools
  • Build a LangChain agent that can interact with Geoapify
  • 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 Geoapify MCP server, and what's possible with it?

The Geoapify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Geoapify account. It provides structured and secure access to powerful location-based services, so your agent can perform actions like geocoding addresses, generating routes, fetching map tiles, and analyzing geographic data on your behalf.

  • Address autocomplete and geocoding: Instantly convert partial or full addresses into geographic coordinates, or fetch smart suggestions to speed up location entry.
  • Routing and reachability analysis: Generate routes, calculate reachable areas (isochrones/isodistances), and let your agent determine how far you can travel from a point within a set time or distance.
  • IP-based geolocation: Look up the approximate location of any IP address to enrich user data, personalize experiences, or detect regions automatically.
  • Map visualization and customization: Fetch custom-styled map tiles and create personalized marker icons for fully tailored map displays in your applications or reports.
  • Boundary and geometry operations: Retrieve administrative boundaries for any place or coordinate, and perform advanced geometric operations like combining or intersecting polygons to analyze spatial relationships.

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 step10 STEPS
1

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
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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters 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/core is the core agent framework
  • dotenv/config loads environment variables
4

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
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Geoapify functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
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 Geoapify tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['geoapify']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Geoapify 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 Geoapify tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "geoapify-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Geoapify MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Geoapify tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

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

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept 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 invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['geoapify']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "geoapify-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Geoapify related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Geoapify 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.
TOOLS

Supported Tools

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

Address Autocomplete

Tool to fetch address suggestions based on partial input.

Batch Requests

Create or retrieve asynchronous batch processing jobs for geocoding, reverse geocoding, routing, or isoline APIs.

Get Boundaries Containing Location

Retrieve all administrative boundaries that contain a given location.

Create Batch Forward Geocode Job

Tool to create a batch forward geocoding job for up to 1000 addresses.

Create Batch Reverse Geocode Job

Tool to create a batch reverse geocoding job that converts multiple lat/lon coordinates into addresses asynchronously.

Forward Geocoding

Tool to convert an address into geographic coordinates.

Geometry Operation

Tool to perform geometric operations on stored polygon geometries.

Get Batch Forward Geocode Results

Retrieve completed batch forward geocoding results in JSON using a job ID.

Get Batch Reverse Geocode Results

Tool to retrieve batch reverse geocoding job results.

Get Child Boundaries (Consists Of)

Get boundaries that a specified location consists of.

Get Map Style JSON

Tool to retrieve vector map style JSON for MapLibre GL and Mapbox GL.

Generate Static Map Image

Tool to generate static map images with customizable style, size, center, zoom, markers, and geometries.

IP Geolocation

Lookup geographic location information for an IP address.

Generate isoline (isochrone/isodistance)

Tool to generate isochrone or isodistance isolines.

List Postcodes

Tool to list postcodes within a specified area or boundary.

Map Matching

Snap GPS traces to the road network for accurate route reconstruction.

Fetch Geoapify Map Tiles

Tool to fetch raster map tiles or style JSON from Geoapify.

Create Marker Icon

Generate custom map marker icons as PNG images.

Place Details

Tool to retrieve detailed information about a specific place.

Places Search

Search for points of interest (POIs) like restaurants, hotels, attractions, hospitals, etc.

Postcode Search

Tool to retrieve postcode information for a location.

Reverse Geocoding

Tool to reverse geocode coordinates into a structured address.

Route Matrix

Compute travel time and distance matrices between origin and destination coordinates.

Route Planner

Optimize multi-agent routes for deliveries, pickups, and service jobs.

Routing

Tool to calculate routes between multiple waypoints.

FRAMEWORKS

How to build Geoapify MCP Agent with another framework

Claude Code logo

Claude Code

Use Geoapify MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Geoapify MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Geoapify MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Geoapify MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Geoapify MCP with Grok Bot

Codex logo

Codex

Use Geoapify MCP with Codex

OpenClaw logo

OpenClaw

Use Geoapify MCP with OpenClaw

Hermes logo

Hermes

Use Geoapify MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Geoapify MCP with Atomic Agent

Google ADK logo

Google ADK

Use Geoapify MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Geoapify MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Geoapify MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Geoapify MCP with LlamaIndex

CrewAI logo

CrewAI

Use Geoapify MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Geoapify MCP with Pydantic AI

AutoGen logo

AutoGen

Use Geoapify MCP with AutoGen

FAQ

Frequently asked questions

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

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 Geoapify tools.

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

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