# How to integrate La Growth Machine MCP with LangChain

```json
{
  "title": "How to integrate La Growth Machine MCP with LangChain",
  "toolkit": "La Growth Machine",
  "toolkit_slug": "lagrowthmachine",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/lagrowthmachine/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/lagrowthmachine/framework/langchain.md",
  "updated_at": "2026-03-29T06:39:56.150Z"
}
```

## Introduction

This guide walks you through connecting La Growth Machine to LangChain using the Composio tool router. By the end, you'll have a working La Growth Machine agent that can launch a multi-channel campaign for new leads, get outreach stats for this week's campaigns, add a contact to your sales pipeline through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a La Growth Machine account through Composio's La Growth Machine MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate La Growth Machine with

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

## TL;DR

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LAGROWTHMACHINE_ADD_RB2B_VISITOR_TO_AUDIENCE` | Add RB2B Visitor to Audience | Tool to add RB2B website visitor to a LaGrowthMachine audience via native webhook. Use when you need to push identified website visitors from RB2B into a specific audience for outreach campaigns. |
| `LAGROWTHMACHINE_CREATE_AUDIENCE_FROM_LINKEDIN_URL` | Create Audience from LinkedIn URL | Tool to import leads into La Growth Machine audiences from LinkedIn URLs. Accepts LinkedIn Regular search URLs, Sales Navigator search URLs, or LinkedIn post URLs. Requires specifying the identity to impersonate and the audience name to populate. |
| `LAGROWTHMACHINE_CREATE_INBOX_WEBHOOK` | Create Inbox Webhook | Tool to create an inbox webhook for real-time notifications. Use when you need to receive notifications about LinkedIn and Email messages sent or received by leads in La Growth Machine campaigns. |
| `LAGROWTHMACHINE_CREATE_OR_UPDATE_LEAD` | Create or Update Lead | Tool to create or update a lead in LaGrowthMachine. Requires audience plus at least one identifier: proEmail, persoEmail, linkedinUrl, twitter, or firstname+lastname with companyUrl/companyName. Use leadId to update an existing lead. |
| `LAGROWTHMACHINE_DELETE_INBOX_WEBHOOK` | Delete Inbox Webhook | Tool to delete an existing inbox webhook by its ID. Use when you need to stop receiving inbox events at the webhook URL. |
| `LAGROWTHMACHINE_GET_CAMPAIGNS` | Get Campaigns | Tool to retrieve all campaigns from LaGrowthMachine with pagination support. Use when you need to list campaigns, with optional skip and limit parameters for pagination (max 25 per page). |
| `LAGROWTHMACHINE_LIST_AUDIENCES` | List Audiences | Tool to list all audiences in your LaGrowthMachine account. Use when you need to retrieve audience details including ID, name, description, size, type, and source URL. |
| `LAGROWTHMACHINE_LIST_IDENTITIES` | List Identities | Tool to list all connected identities in your LaGrowthMachine account. Use when you need to retrieve identity IDs for sending LinkedIn or Email messages through other APIs. |
| `LAGROWTHMACHINE_LIST_INBOX_WEBHOOKS` | List Inbox Webhooks | Tool to list all inbox webhooks currently configured in your workspace. Use when you need to retrieve webhook IDs, names, and target URLs for webhook management or audit purposes. |
| `LAGROWTHMACHINE_LIST_MEMBERS` | List Members | Tool to list all members (users) associated with your workspace. Use when you need to retrieve member information, especially memberId which is required for action-based endpoints like sending LinkedIn or Email messages. |
| `LAGROWTHMACHINE_REGISTER_VECTOR_VISITOR_WEBHOOK` | Register Vector Visitor Webhook | Tool to register Vector website visitors to a La Growth Machine audience. Use when receiving visitor events from Vector integration to automatically add identified contacts to the specified audience. |
| `LAGROWTHMACHINE_REMOVE_LEAD_FROM_AUDIENCES` | Remove Lead From Audiences | Tool to remove a lead from one or more specified audiences in La Growth Machine. Use when you need to unsubscribe or remove a lead from audience lists. |
| `LAGROWTHMACHINE_SEARCH_LEAD` | Search Lead | Tool to search for a lead using various criteria. Use when you need to find a lead by email, LinkedIn URL, lead ID, or name combination. At least one of these must be provided: email, linkedinUrl, leadId, or firstname+lastname+(companyName or companyUrl). |

## Supported Triggers

None listed.

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

The La Growth Machine MCP server is an implementation of the Model Context Protocol that connects your AI agent to La Growth Machine. It provides structured and secure access so your agent can perform La Growth Machine 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 La Growth Machine 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 La Growth Machine 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 La Growth Machine tools as needed
```python
# Create Tool Router session for La Growth Machine
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['lagrowthmachine']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "lagrowthmachine-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({
    "lagrowthmachine-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 La Growth Machine 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 La Growth Machine 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=['lagrowthmachine']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "lagrowthmachine-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 La Growth Machine 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: ['lagrowthmachine']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "lagrowthmachine-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 La Growth Machine 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 La Growth Machine 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 La Growth Machine MCP Agent with another framework

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

## Related Toolkits

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- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
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- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
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- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [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.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Basin](https://composio.dev/toolkits/basin) - Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [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.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and La Growth Machine MCP?

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

### Can I manage the permissions and scopes for La Growth Machine while using Tool Router?

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)