How to integrate Icypeas MCP with LangChain

This guide walks you through connecting Icypeas to LangChain using the Composio tool router. By the end, you'll have a working Icypeas agent that can find verified email for john doe at acme.com, bulk search emails for 100 new leads, list all role-based emails at example.org through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Icypeas account through Composio's Icypeas MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Icypeas is an email discovery and verification service for professionals. It helps you find and verify work email addresses quickly and reliably.

22 Tools

Introduction

This guide walks you through connecting Icypeas to LangChain using the Composio tool router. By the end, you'll have a working Icypeas agent that can find verified email for john doe at acme.com, bulk search emails for 100 new leads, list all role-based emails at example.org through natural language commands.

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

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

Also integrate Icypeas with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

The Icypeas MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Icypeas account. It provides structured and secure access to professional email discovery and verification, so your agent can perform actions like finding emails, verifying addresses, searching company data, and scanning domains on your behalf.

  • Accurate email discovery and verification: Instantly find and verify professional email addresses using first name, last name, and company domain to supercharge your outreach or lead generation.
  • Bulk prospecting and search management: Launch bulk email or profile URL searches for thousands of contacts at once, then track progress and fetch results without manual oversight.
  • Comprehensive company and people lookup: Search for companies or filter people by name, title, company, and more to enrich your CRM or build targeted prospect lists efficiently.
  • Domain scanning for role-based emails: Scan entire company domains to discover all available role-based email addresses, simplifying large-scale contact discovery.
  • Subscription and usage insights: Check your Icypeas subscription details and remaining credits, helping you stay on top of your usage and plan outreach campaigns smarter.

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 Icypeas 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 Icypeas 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: ['icypeas']
    }
);

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

Configure the agent with the MCP URL

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

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

Bulk Email Search

Initiate a bulk email search job to find professional email addresses for multiple people at once.

Find Profile URLs Bulk

Tool to perform bulk search for profile URLs based on firstname, lastname, and company/domain or job title.

Bulk Reverse Email Lookup

Tool to find LinkedIn profile URLs for multiple professional email addresses in a single request.

Scrape Bulk

Tool to scrape multiple LinkedIn profiles or companies in bulk (up to 50 per request).

Check Search Progress

Check the processing progress of a search by its ID.

Count Companies

Tool to count companies in Icypeas database matching specified filters without returning data or being charged.

Count People

Tool to count people matching specified filters without retrieving data or consuming credits.

Domain Scan

Tool to scan a domain for role-based email addresses.

Fetch Bulk Search Info

Retrieve bulk search files with their status and progress.

Fetch Subscription Information

Retrieves subscription details and remaining credits for an Icypeas account.

Find Companies

Tool to search companies in Icypeas database.

Find Company URL

Tool to find a single company profile URL using a company name or domain.

Reverse Email Lookup

Find the LinkedIn profile URL behind a single professional email address.

Find People

Search for people/leads in the Icypeas database.

Find Profile URL

Finds a person's LinkedIn profile URL using their name and company or job title.

Find Single Email

Initiates an asynchronous email search to find a prospect's email address using their name and company.

Statistics Bulk Search

Tool to parse bulk search statistics webhook.

Retrieve Search Results

Tool to retrieve the results of a search by ID or to paginate through bulk search results.

Scrape Company

Tool to initiate scraping of a LinkedIn company page.

Scrape Profile

Tool to initiate scraping of a LinkedIn profile.

Setup Notifications

Provides instructions for setting up Icypeas push notifications/webhooks.

Verify Email Address

Tool to verify if a specific email address exists and is valid.

FRAMEWORKS

How to build Icypeas MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Icypeas MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Icypeas MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Icypeas MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Icypeas MCP with Claude Cowork

Codex logo

Codex

Use Icypeas MCP with Codex

OpenClaw logo

OpenClaw

Use Icypeas MCP with OpenClaw

Hermes logo

Hermes

Use Icypeas MCP with Hermes

CLI logo

CLI

Use Icypeas MCP with CLI

Google ADK logo

Google ADK

Use Icypeas MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Icypeas MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Icypeas MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Icypeas MCP with LlamaIndex

CrewAI logo

CrewAI

Use Icypeas MCP with CrewAI

FAQ

Frequently asked questions

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

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

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Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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