# How to integrate LeadBoxer MCP with OpenAI Agents SDK

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

## Introduction

This guide walks you through connecting LeadBoxer to the OpenAI Agents SDK 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 OpenAI Agents SDK 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)
- [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)
- [LangChain](https://composio.dev/toolkits/leadboxer/framework/langchain)
- [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
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for LeadBoxer
- Configure an AI agent that can use LeadBoxer as a tool
- Run a live chat session where you can ask the agent to perform LeadBoxer operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## 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

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live LeadBoxer project
- Some knowledge of Python or Typescript

### 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).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like LeadBoxer.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only leadboxer.
- The router checks the user's LeadBoxer connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access LeadBoxer.
- This approach keeps things lightweight and lets the agent request LeadBoxer tools only when needed during the conversation.
```python
# Create a LeadBoxer Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["leadboxer"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for LeadBoxer
const session = await composio.create(userId as string, {
  toolkits: ['leadboxer'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access LeadBoxer. "
        "Help users perform LeadBoxer operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access LeadBoxer. Help users perform LeadBoxer operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["leadboxer"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access LeadBoxer. "
        "Help users perform LeadBoxer operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['leadboxer'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access LeadBoxer. Help users perform LeadBoxer operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\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

This was a starter code for integrating LeadBoxer MCP with OpenAI Agents SDK to build a functional AI agent that can interact with LeadBoxer.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## 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)
- [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)
- [LangChain](https://composio.dev/toolkits/leadboxer/framework/langchain)
- [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)

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- [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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

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