# How to integrate LeadBoxer MCP with LangChain

```json
{
  "title": "How to integrate LeadBoxer MCP with LangChain",
  "toolkit": "LeadBoxer",
  "toolkit_slug": "leadboxer",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/leadboxer/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/leadboxer/framework/langchain.md",
  "updated_at": "2026-03-29T06:40:06.775Z"
}
```

## Introduction

This guide walks you through connecting LeadBoxer to LangChain using the Composio tool router. By the end, you'll have a working LeadBoxer agent that can list all new leads from today, show all companies visiting pricing page, get contact info for most recent lead through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a LeadBoxer account through Composio's LeadBoxer MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate LeadBoxer with

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

## TL;DR

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LEADBOXER_ADD_OR_UPDATE_LEAD_TAGS` | Add or Update Lead Tags | Tool to add or update lead tags in LeadBoxer. Use when you need to manage lead tags by adding new tags, removing specific tags, or overwriting all existing tags for a specified user. |
| `LEADBOXER_DELETE_CTD` | Delete Custom Tracking Domain | Tool to delete a custom tracking domain entry for a dataset. Use when you need to remove a specific custom tracking domain (CTD) associated with a dataset in LeadBoxer. |
| `LEADBOXER_GET_EVENTS` | Get Events | Tool to fetch events for specified sessions from LeadBoxer. Use when you need to retrieve behavioral data including pageviews, clicks, form submissions, email interactions, and custom events. Events can be filtered by session ID, email, user ID, or segment/smartlist IDs. |
| `LEADBOXER_GET_LEAD_SCORE_FORMULA` | Get Lead Score Formula | Tool to fetch the lead score formula for a specific dataset. Use when you need to understand how lead scores are calculated for records in a dataset. The formula defines scoring based on criteria types: Range (number ranges), Match (exact values), Exists (presence of values), and Boost (event-based scoring). |
| `LEADBOXER_GET_SESSIONS` | Get Sessions | Tool to fetch sessions for a specified lead ID from LeadBoxer. Use when you need to retrieve session data for a user, with optional filtering by email, user ID, Smartlist ID, or segment ID. A session represents a single visit to the site, and users can have multiple sessions over time. |
| `LEADBOXER_LOG_SERVER_SIDE_EVENT` | Log Server-Side Event | Tool to track server-side events in LeadBoxer. Use when tracking backend events, page views, or custom activities from your server. This endpoint supports tracking user interactions, conversions, and other activities that occur on the server-side. |
| `LEADBOXER_GET_CUSTOM_TRACKING_DOMAINS` | Get Custom Tracking Domains | Tool to fetch custom tracking domain entries for a dataset. Use when you need to retrieve all custom tracking domains that are created or in progress for a specific datasetId. |
| `LEADBOXER_POST_EVENT_DATA` | Post Event Data | Tool to send event data for tracking user activities via POST request. Use when tracking events by sending data in the request body with application/x-www-form-urlencoded format. |
| `LEADBOXER_GET_LEAD_DETAIL` | Get Lead Detail | Tool to fetch detailed information about a lead based on filters. Use when you need comprehensive lead data for a specific lead ID. The default view type is B2B. Note: On initial pageview, there may be a few seconds overhead before data is populated; consider implementing a 3-second delay after lead creation. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "leadboxer-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({
    "leadboxer-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 LeadBoxer 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 LeadBoxer 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=['leadboxer']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "leadboxer-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 LeadBoxer 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: ['leadboxer']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "leadboxer-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 LeadBoxer 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 LeadBoxer 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 LeadBoxer MCP Agent with another framework

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

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [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.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [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.
- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [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.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [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.
- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and LeadBoxer MCP?

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

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

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

---
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