# How to integrate Botstar MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Botstar MCP with OpenAI Agents SDK",
  "toolkit": "Botstar",
  "toolkit_slug": "botstar",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/botstar/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/botstar/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:03:49.150Z"
}
```

## Introduction

This guide walks you through connecting Botstar to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Botstar agent that can open live chat widget for new visitor, update user profile in current chat session, retrieve chatbot application id for setup through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Botstar account through Composio's Botstar MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Botstar with

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

The Botstar MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Botstar account. It provides structured and secure access to your chatbot operations, so your agent can perform actions like managing live chat sessions, updating user details, retrieving app parameters, and sending data between webviews and your bot—all on your behalf.
- Live chat session control: Programmatically open, close, or reinitialize the Botstar live chat widget to manage user interactions in real time.
- Automated user profile updates: Let your agent update user details and profile attributes during an active chatbot conversation for a more personalized experience.
- Webview data exchange: Seamlessly send responses from webviews back to the chatbot or retrieve parameters passed from the bot to your webview for dynamic content handling.
- Custom callback registration: Set up onOpen and onClose event handlers so your agent can trigger actions whenever users interact with the chat window.
- Application ID and configuration retrieval: Fetch essential Botstar application IDs and parameters for smooth widget initialization and advanced bot customization.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BOTSTAR_CREATE_BOT` | Create Bot | Tool to create a new bot in BotStar. Use when you need to create a new bot instance with a specific name. |
| `BOTSTAR_CREATE_BOT_ATTRIBUTE` | Create Bot Attribute | Tool to create a new bot attribute in BotStar. Bot attributes are global variables for a bot and support multilingual values. Use when you need to define custom data fields for your bot. |
| `BOTSTAR_CREATE_CMS_ENTITY` | Create CMS Entity | Tool to create a CMS entity in BotStar with a name and optional fields. Use when you need to define a new content structure with custom fields supporting various data types. |
| `BOTSTAR_CREATE_ENTITY_FIELDS` | Create Entity Fields | Tool to create entity field(s) in BotStar CMS. Supports multiple field types including text, multiple_values, single_option, multiple_options, image, date, and entity. Use when you need to add new fields to an existing entity. |
| `BOTSTAR_CREATE_ENTITY_ITEM` | Create Entity Item | Tool to create a new entity item in BotStar CMS. Use when adding items to a CMS entity with custom field values. |
| `BOTSTAR_CREATE_USER_ATTRIBUTES` | Create User Attributes | Tool to create custom user attributes in BotStar. Use when you need to define new custom attributes for users with specified field name and type. |
| `BOTSTAR_DELETE_BOT_ATTRIBUTE` | Delete Bot Attribute | Tool to delete a bot attribute by ID. Use when you need to remove a custom attribute from a bot. |
| `BOTSTAR_DELETE_CMS_ENTITY` | Delete CMS Entity | Tool to delete a CMS entity by ID. Use when you need to remove an entity from the bot's content management system. |
| `BOTSTAR_DELETE_ENTITY_FIELDS` | Delete Entity Fields | Tool to delete entity field(s) from a CMS entity. Use when you need to remove fields from a CMS entity by their unique names. |
| `BOTSTAR_DELETE_ENTITY_ITEM` | Delete Entity Item | Tool to delete an entity item from a CMS entity. Use when you need to remove a specific item from a bot's CMS entity. |
| `BOTSTAR_GET_BOT` | Get Bot | Tool to get your bot by bot ID. Use when you need detailed bot information including ID, name, and team name. |
| `BOTSTAR_GET_BOT_APP_ID` | Get BotStar Application IDs | Tool to retrieve the BotStar application ID (`appId`). Use when initializing or reinitializing the live chat widget. |
| `BOTSTAR_GET_CMS_ENTITY` | Get CMS Entity | Tool to get a specific CMS entity by ID. Returns entity details including fields configuration. Use when you need to retrieve metadata about a CMS entity structure. |
| `BOTSTAR_GET_ENTITY_ITEM` | Get Entity Item | Tool to retrieve a specific item from a CMS entity with all field values. Use when you need to get detailed information about a single entity item. |
| `BOTSTAR_LIST_BOT_ATTRIBUTES` | List Bot Attributes | Tool to get all bot attributes from BotStar. Returns array of bot attributes with id, name, desc, value, and data_type. Use when you need to retrieve or inspect all attributes configured for a bot. |
| `BOTSTAR_LIST_BOTS` | List Bots | Tool to get your list of bots. Use when you need to retrieve all bots associated with your account. Returns an array of bots with their id, name, and team_name. |
| `BOTSTAR_LIST_CMS_ENTITIES` | List CMS Entities | Tool to retrieve all CMS entities for a bot. Use when you need to access entity definitions, field configurations, or available entity schemas. |
| `BOTSTAR_LIST_ENTITY_ITEMS` | List Entity Items | Tool to retrieve all entity items with pagination support. Use when you need to list CMS entity items, with optional filtering by name and status. |
| `BOTSTAR_LIVECHAT_BOOT` | Livechat boot | Tool to reinitialize the live chat widget with provided data. Use after initial load to reset or update widget configuration. |
| `BOTSTAR_LIVECHAT_CLOSE` | Close BotStar Livechat Widget | Tool to hide the live chat window. Use when the chat widget is configured in livechat or popup mode. |
| `BOTSTAR_BOTSTAR_LIVECHAT_ON_CLOSE` | BotStar LiveChat onClose Callback | Tool to register a callback when the chat window is closed. Use after the widget is initialized. Example prompt: "Register an onClose handler that logs 'Goodbye!' to the console." |
| `BOTSTAR_LIVECHAT_ON_OPEN` | Livechat on open | Tool to register a callback when the chat window is opened. Use after widget initialization. |
| `BOTSTAR_LIVECHAT_OPEN` | Livechat open | Tool to show the live chat window. Use after the widget has been bootstrapped with BotStarApi('boot') to programmatically open the chat window (mode must be 'livechat' or 'popup'). |
| `BOTSTAR_LIVECHAT_UPDATE` | Livechat update | Tool to update user details on the current live chat session. Use when you need to modify user profile attributes during an active conversation. |
| `BOTSTAR_PUBLISH_BOT` | Publish Bot to Live | Tool to publish a bot to live. Use when you need to deploy changes to the production environment. |
| `BOTSTAR_UPDATE_BOT_ATTRIBUTE` | Update Bot Attribute | Tool to update a bot attribute in BotStar. Use when you need to modify the description or value of a bot attribute with optional multilingual support. |
| `BOTSTAR_UPDATE_CMS_ENTITY` | Update CMS Entity | Tool to update a CMS entity in BotStar. Use when you need to modify the name or configuration of an existing CMS entity. |
| `BOTSTAR_UPDATE_ENTITY_FIELDS` | Update Entity Fields | Tool to update entity field(s) in BotStar CMS. Use when you need to modify the name or options of existing fields. |
| `BOTSTAR_UPDATE_ENTITY_ITEM` | Update Entity Item | Tool to update a CMS entity item in BotStar. Use when you need to modify the name, status, or custom field values of an entity item. |
| `BOTSTAR_WEBVIEW_GET_PARAMETER` | Get BotStar Webview Parameter | Tool to retrieve a parameter value passed from the BotStar chatbot to the webview. Use inside onChatBotReady after your page loads in modal mode with bs:input meta tags. |
| `BOTSTAR_WEBVIEW_SEND_RESPONSE` | Webview send response | Tool to send data from the webview back to the BotStar chatbot. Use when you need to transmit responses or custom outputs from an open webview. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

## Related Toolkits

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

## Frequently Asked Questions

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

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

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

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

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