# How to integrate Bouncer MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Bouncer MCP with OpenAI Agents SDK",
  "toolkit": "Bouncer",
  "toolkit_slug": "bouncer",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/bouncer/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/bouncer/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-06T08:03:42.497Z"
}
```

## Introduction

This guide walks you through connecting Bouncer to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Bouncer agent that can verify this email address instantly, check domain validity for new signups, batch-verify a list of customer emails through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Bouncer account through Composio's Bouncer MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Bouncer with

- [Claude Agent SDK](https://composio.dev/toolkits/bouncer/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/bouncer/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/bouncer/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/bouncer/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/bouncer/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/bouncer/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/bouncer/framework/cli)
- [Google ADK](https://composio.dev/toolkits/bouncer/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/bouncer/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/bouncer/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/bouncer/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/bouncer/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/bouncer/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 Bouncer
- Configure an AI agent that can use Bouncer as a tool
- Run a live chat session where you can ask the agent to perform Bouncer 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 Bouncer MCP server, and what's possible with it?

The Bouncer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bouncer account. It provides structured and secure access to your email verification and validation tools, so your agent can perform actions like real-time email validation, bulk verification, domain checks, and toxicity analysis for improved email deliverability.
- Real-time email verification: Instantly validate single email addresses to check deliverability and reduce bounce rates before sending messages.
- Bulk batch verification: Initiate, manage, and retrieve results from batch email verification jobs to clean and maintain large email lists efficiently.
- Toxicity analysis of email lists: Start and monitor toxicity analysis jobs to identify potentially harmful or problematic email addresses in your database.
- Domain verification: Check the validity and configuration of email domains, including MX records and catch-all status, to ensure emails reach their intended targets.
- Automated batch management: Finish, delete, or update batch verification and toxicity jobs to keep your verification workflows tidy and up-to-date.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BOUNCER_CHECK_TOXICITY_LIST_JOB_STATUS` | Check Toxicity List Job Status | Tool to check the status of a specific toxicity list job. use after creating a toxicity list job to poll its status until completion. |
| `BOUNCER_CREATE_BATCH_REQUEST` | Create Batch Request | Tool to initiate a batch email verification request. use when you have multiple emails to verify in one api call. returns a batch id and initial status. |
| `BOUNCER_CREATE_TOXICITY_LIST_JOB` | Create Toxicity List Job | Tool to create a toxicity analysis job for a list of email addresses. use when you need to batch-process toxicity checks for multiple emails at once. |
| `BOUNCER_DELETE_BATCH_REQUEST` | Delete batch request | Tool to delete a batch verification request. use when you need to remove all associated emails and results for a specific batch after confirming that the batch data is no longer required. |
| `BOUNCER_DELETE_TOXICITY_LIST_JOB` | Delete Toxicity List Job | Tool to delete a specific toxicity list job. use when you need to remove a completed or unwanted toxicity analysis job after confirming its id. |
| `BOUNCER_FINISH_BATCH` | Finish Batch | Tool to mark a batch verification process as finished. use after batch processing completes to stop further verifications and reclaim unused credits. |
| `BOUNCER_GET_BATCH_RESULTS` | Get Batch Results | Tool to retrieve the results of a batch verification process. use after submitting a batch to fetch all processed email verification outcomes. |
| `BOUNCER_VERIFY_DOMAIN` | Verify Domain | Tool to verify the validity and configuration of a domain. use when you need to confirm the domain's mx records and catch-all behavior. |
| `BOUNCER_VERIFY_EMAIL` | Verify Email | Tool to verify a single email address in real-time. use when validating email entry form inputs instantly. |

## Supported Triggers

None listed.

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

The Bouncer MCP server is an implementation of the Model Context Protocol that connects your AI agent to Bouncer. It provides structured and secure access so your agent can perform Bouncer 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 Bouncer 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 Bouncer.
```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 bouncer.
- The router checks the user's Bouncer connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Bouncer.
- This approach keeps things lightweight and lets the agent request Bouncer tools only when needed during the conversation.
```python
# Create a Bouncer Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bouncer"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Bouncer
const session = await composio.create(userId as string, {
  toolkits: ['bouncer'],
});
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 Bouncer. "
        "Help users perform Bouncer 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 Bouncer. Help users perform Bouncer 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=["bouncer"]
)
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 Bouncer. "
        "Help users perform Bouncer 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: ['bouncer'],
  });
  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 Bouncer. Help users perform Bouncer 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 Bouncer MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Bouncer.
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 Bouncer MCP Agent with another framework

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

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## Frequently Asked Questions

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

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

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

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

---
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