How to integrate Companyenrich MCP with LangChain

This guide walks you through connecting Companyenrich to LangChain using the Composio tool router. By the end, you'll have a working Companyenrich agent that can enrich openai company profile by domain, find companies similar to stripe, search cybersecurity startups in berlin through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Companyenrich account through Composio's Companyenrich MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Companyenrich logoCompanyenrich
Api Key

Companyenrich is a company data API for enrichment, search, and similar company discovery. Use it to turn domains or company names into clean business profiles fast.

32 Tools

Introduction

This guide walks you through connecting Companyenrich to LangChain using the Composio tool router. By the end, you'll have a working Companyenrich agent that can enrich openai company profile by domain, find companies similar to stripe, search cybersecurity startups in berlin through natural language commands.

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

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

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TL;DR

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

The Companyenrich MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Companyenrich account. It provides structured and secure access so your agent can perform Companyenrich operations on your behalf.

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 Companyenrich 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 Companyenrich 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: ['companyenrich']
    }
);

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

Configure the agent with the MCP URL

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

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

Autocomplete Companies

Returns a list of companies matching the given partial domain name.

Autocomplete Keywords

Lookup keywords for use in company search filters.

Autocomplete Positions

Lookup positions/job titles for use in people search filters.

Autocomplete Technologies

Lookup technologies for use in company search filters.

Count companies matching search criteria

Returns the total count of companies matching the given search criteria without retrieving the actual results.

Count Similar Companies

Tool to count the total number of similar companies matching the given search criteria without retrieving the actual results.

Create people search export job

Creates an asynchronous search export job for up to 50,000 people.

Create search export job

Creates an asynchronous search export job for company data.

Enrich company by domain

Enriches a company using its domain name as lookup parameter.

Enrich company by properties

Enriches a company using its properties.

Batch Enrich Companies

Enriches a list of companies using their domain names.

Find Similar Companies

Tool to find similar companies to the given company by domain.

Get Bulk Enrichment Job Status

Returns the current status of a bulk enrichment job.

Get Company Workforce

Returns workforce insights for a single company.

Get Country by Code

Tool to search for a country by its ISO 3166-1 alpha-2 code.

Get Current User

Returns information about the authenticated user, including their API key, credit balance, and account capabilities.

Get Job Details

Returns details for a specific job by ID.

Get People Search Export Job Status

Returns the current status of a person search export job.

Get Regions

Tool to get all available regions.

Get search export job status

Returns the current status of a search export job.

List all jobs

Returns a paginated list of all jobs (bulk enrichment, etc.

List bulk enrichment jobs

Returns a paginated list of all bulk enrichment jobs for the authenticated user.

List Industries

Obtain a list of all company industries.

List Person Search Export Jobs

Returns a paginated list of all person search export jobs for the authenticated user.

List search export jobs

Returns a paginated list of all search export jobs for the authenticated user.

Lookup Person by Email

Look up a person by email address.

Search people with cursor pagination

Searches people based on given criteria using cursor-based pagination.

Search cities by name or country

Search for cities by name or country codes.

Search companies by criteria

Searches companies based on given criteria.

Search Countries

Tool to search countries by name.

Search People

Searches people based on given criteria using page-based pagination.

Search States

Tool to search states by name or country codes.

FAQ

Frequently asked questions

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

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

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