How to integrate Yandex MCP with LangChain

This guide walks you through connecting Yandex to LangChain using the Composio tool router. By the end, you'll have a working Yandex agent that can find walking route from red square to gorky park, look up a business by address in moscow, get map tiles for downtown saint petersburg through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Yandex account through Composio's Yandex MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Yandex is a leading Russian internet services provider offering search, email, maps, and more. It's known for robust email, navigation, and web-based solutions tailored for Russian-speaking users.

21 Tools

Introduction

This guide walks you through connecting Yandex to LangChain using the Composio tool router. By the end, you'll have a working Yandex agent that can find walking route from red square to gorky park, look up a business by address in moscow, get map tiles for downtown saint petersburg through natural language commands.

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

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

Also integrate Yandex with

TL;DR

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

The Yandex MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Yandex account. It provides structured and secure access to Yandex search, maps, and business information, so your agent can perform actions like business lookup, reverse geocoding, detailed route planning, and retrieving map tiles on your behalf.

  • Business and organization search: Instantly find businesses or organizations by name, address, or tax ID—perfect for regional lookups and company discovery.
  • Reverse geocoding for precise locations: Translate latitude and longitude into street addresses or place names using Yandex Maps, making it easy to identify places from coordinates.
  • Detailed route generation: Let your agent plan step-by-step driving, walking, or public transportation routes between two points, complete with directions and travel options.
  • Custom map tile retrieval: Fetch specific map tile images by their coordinates and zoom level, enabling custom visualizations or interactive map experiences.

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 Yandex 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 Yandex 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: ['yandex']
    }
);

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

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "yandex-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 Yandex MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Yandex 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 Yandex 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 Yandex 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: ['yandex']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "yandex-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 Yandex 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 Yandex 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 Yandex action and event your agent gets out of the box.

Reverse Geocode Coordinates

Tool to convert geographic coordinates to a human-readable address (reverse geocoding).

Get Account Experiments

Tool to retrieve Yandex Music account experimental features and A/B testing flags.

Get Account Status

Tool to retrieve Yandex Music account status and permissions.

Get Music Genres

Tool to retrieve the list of music genres from Yandex Music.

Get Permission Alerts

Tool to retrieve permission alerts and notifications from Yandex Music API.

Get Playlists by Tag

Tool to retrieve playlist IDs associated with a specific tag.

Get Public Resource Metadata

Tool to retrieve metadata for a public file or folder on Yandex Disk.

Get Public Resource Download Link

Tool to get a direct download link for a publicly shared Yandex Disk resource.

Get Rotor Account Status

Tool to retrieve authenticated user's rotor account status with supplementary fields.

Get Rotor Stations Dashboard

Tool to retrieve recommended radio stations for the current user.

Get Yandex Music Settings

Tool to retrieve Yandex Music settings including available purchase products and payment configuration.

Get Yandex Music Stations List

Tool to retrieve all radio stations with user settings from Yandex Music.

Get Track Download Info

Tool to retrieve available download options for a Yandex Music track.

List Filters

Tool to retrieve all filters configured for a Yandex Metrica counter.

List Goals

Tool to retrieve all goals configured for a Yandex Metrica counter.

List Counter Grants

Tool to retrieve the list of permissions (grants) for a Yandex Metrica counter.

List Log Requests

Tool to retrieve a list of log requests for a Yandex Metrica counter.

List Storage Buckets

Tool to list all Yandex Object Storage buckets owned by the authenticated user.

Organization Search

Tool to find businesses and organizations by name, address, or TIN.

Generate detailed route

Tool to generate detailed route for driving, walking, or public transport.

Yandex Tiles API

Tool to fetch individual map tile images by x/y coordinates and zoom level.

FAQ

Frequently asked questions

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

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

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