# How to integrate Rocket reach MCP with LangChain

```json
{
  "title": "How to integrate Rocket reach MCP with LangChain",
  "toolkit": "Rocket reach",
  "toolkit_slug": "rocket_reach",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/rocket_reach/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/rocket_reach/framework/langchain.md",
  "updated_at": "2026-05-12T10:24:18.572Z"
}
```

## Introduction

This guide walks you through connecting Rocket reach to LangChain using the Composio tool router. By the end, you'll have a working Rocket reach agent that can find verified email for linkedin profile, get direct dial number for company executive, lookup job title for specific contact through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Rocket reach account through Composio's Rocket reach MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Rocket reach with

- [OpenAI Agents SDK](https://composio.dev/toolkits/rocket_reach/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/rocket_reach/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/rocket_reach/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/rocket_reach/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/rocket_reach/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/rocket_reach/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/rocket_reach/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/rocket_reach/framework/cli)
- [Google ADK](https://composio.dev/toolkits/rocket_reach/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/rocket_reach/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/rocket_reach/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/rocket_reach/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/rocket_reach/framework/crew-ai)

## TL;DR

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

The Rocket reach MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your RocketReach account. It provides structured and secure access to professional contact information, so your agent can perform actions like finding verified emails, enriching lead profiles, searching for company details, and managing outreach research—all automatically on your behalf.
- Find verified contact details: Instantly retrieve accurate email addresses, phone numbers, and social profiles for prospects or candidates from the RocketReach database.
- Enrich and update lead profiles: Ask your agent to gather and supplement missing details about leads, including job titles, current companies, and social links.
- Company lookup and research: Have your agent pull company background, industry, size, and key personnel information to inform outreach and targeting strategies.
- List building and segmentation: Let your agent assemble lists of contacts based on filters like company, role, location, or industry, so you can streamline your outreach campaigns.
- Contact verification and scoring: Direct your agent to check the deliverability and accuracy of contact details, helping you prioritize the best leads or candidates.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ROCKET_REACH_CHECK_PERSON_STATUS` | Check Person Status | Tool to check the status of multiple person lookup requests. Use when you need to retrieve the current status of previously initiated person lookups. |
| `ROCKET_REACH_GET_ACCOUNT` | Get RocketReach Account Info | Tool to retrieve account information for the authenticated user. Use when you need to fetch the current user's account details. |
| `ROCKET_REACH_GET_COMPANY_FUNDING` | RocketReach Get Company Funding | Tool to retrieve funding details for a specified company. Use when you need to fetch historical funding rounds by company domain. |
| `ROCKET_REACH_GET_COMPANY_GROWTH` | Get Company Growth Metrics | Tool to get growth metrics for a specified company domain. Use when historical company growth data is needed after confirming the exact company domain. |
| `ROCKET_REACH_GET_COMPANY_INDUSTRIES` | Get Company Industries | Tool to list industries associated with a specified company. Tries multiple RocketReach endpoints using the provided identifier (ID, domain, or name) and extracts industry information from the response payload. |
| `ROCKET_REACH_GET_COMPANY_SIZE` | Get Company Size | Tool to retrieve size metrics of a company. Use when you have a company's domain to get its employee size range. |
| `ROCKET_REACH_GET_COMPANY_TECH_STACK` | Get Company Tech Stack | Tool to get technology stack for a company by domain. Use when you need to discover the tech a company uses after confirming its domain. |
| `ROCKET_REACH_LOOKUP_COMPANY` | RocketReach Lookup Company | Tool to lookup a company's domain via RocketReach Company Lookup API. Use when you need the company domain by name for downstream actions like funding, size, or tech stack. |
| `ROCKET_REACH_LOOKUP_PERSON` | RocketReach Lookup Person | Tool to lookup detailed person information from RocketReach. Use when you need to fetch a person's profile by email. |
| `ROCKET_REACH_LOOKUP_PERSON_AND_COMPANY` | Lookup Person and Company | Tool to lookup both person and company information in a single request. Use when you need comprehensive profile data including employment details. At least one search parameter (name, email, id, linkedin_url, or npi_number) must be provided. |
| `ROCKET_REACH_SEARCH_COMPANIES` | List Companies | Tool to list companies by name or keyword. Use when you need to discover companies matching specific criteria after obtaining an API key. |
| `ROCKET_REACH_SEARCH_PEOPLE` | Search People | Tool to search for people by name, title, or keywords. Use when you need to discover individuals matching specific criteria after obtaining an API key. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Rocket reach MCP server is an implementation of the Model Context Protocol that connects your AI agent to Rocket reach. It provides structured and secure access so your agent can perform Rocket reach operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
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()
```

```typescript
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();
```

### 5. Initialize Composio client

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 Rocket reach tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
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")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Rocket reach 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 Rocket reach tools as needed
```python
# Create Tool Router session for Rocket reach
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['rocket_reach']
)

url = session.mcp.url
```

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

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "rocket_reach-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)
```

```typescript
const client = new MultiServerMCPClient({
    "rocket_reach-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Rocket reach 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")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Rocket reach 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
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=['rocket_reach']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "rocket_reach-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 Rocket reach 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())
```

```typescript
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: ['rocket_reach']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "rocket_reach-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 Rocket reach 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 Rocket reach 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 Rocket reach MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/rocket_reach/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/rocket_reach/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/rocket_reach/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/rocket_reach/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/rocket_reach/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/rocket_reach/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/rocket_reach/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/rocket_reach/framework/cli)
- [Google ADK](https://composio.dev/toolkits/rocket_reach/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/rocket_reach/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/rocket_reach/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/rocket_reach/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/rocket_reach/framework/crew-ai)

## Related Toolkits

- [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools.
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- [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates.
- [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates.
- [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations.
- [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code.
- [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding.
- [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls.
- [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.
- [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Rocket reach MCP?

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

### Can I manage the permissions and scopes for Rocket reach while using Tool Router?

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

---
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