# How to integrate Bart MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Bart MCP with OpenAI Agents SDK",
  "toolkit": "Bart",
  "toolkit_slug": "bart",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/bart/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/bart/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:02:26.975Z"
}
```

## Introduction

This guide walks you through connecting Bart to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Bart agent that can find next departures from embarcadero station, get real-time trip updates for richmond line, check current bart service advisories and alerts through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Bart account through Composio's Bart MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Bart with

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

The Bart MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to BART's public transit data. It provides structured and secure access to real-time schedules, route information, station details, and service advisories, so your agent can plan trips, fetch live updates, check advisories, and explore routes for you.
- Trip planning with live schedules: Instantly retrieve train arrival or departure times and help users plan journeys between any BART stations based on the latest schedule data.
- Live service advisories and alerts: Keep travelers informed by fetching up-to-date system-wide or station-specific service advisories, ensuring users know about delays or disruptions before they travel.
- Route and station discovery: Access detailed information about BART routes and stations, including amenities and configuration, so your agent can answer travel questions or recommend stations.
- Real-time trip and schedule updates: Get the latest trip updates and schedule changes in real time, allowing users to adapt plans quickly if there are changes or issues along their route.
- Access to static and GTFS feeds: Download the latest BART GTFS (General Transit Feed Specification) data for offline schedule planning, analysis, or integration with third-party transit tools.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BART_BART_GET_API_VERSION` | Get BART API Version | Get the current version of the BART API. This action retrieves version information for the BART (Bay Area Rapid Transit) API, including the current API version number, copyright information, and license details. This is useful for verifying API compatibility and ensuring you're working with the expected API version. The BART API is currently at version 3.10 and supports both XML and JSON output formats. Use this action to confirm which version of the API you're interfacing with and to access licensing information. |
| `BART_GET_ELEVATOR_STATUS` | Get Elevator Status | Tool to fetch current elevator status across all BART stations. Use when you need real-time elevator availability information for accessibility planning or route guidance. |
| `BART_GET_ESTIMATED_DEPARTURES` | Get Estimated Departures | Tool to get real-time estimated departure times for a specified BART station. Returns live train departure predictions including minutes until departure, platform assignments, train lengths, line colors, bicycle accommodation, and delay information. Use this when you need current departure times for planning trips or checking train status. |
| `BART_GET_FARE` | Get BART Fare | Get fare information between two BART stations including Clipper and cash prices. Returns multiple fare types (Clipper, cash, senior/disabled, youth, Clipper START) with their respective prices. Use this when you need to find out how much a BART trip costs between two stations. |
| `BART_GET_GTFS_ALERTS` | Get GTFS-RT Service Alerts | Tool to fetch GTFS-RT service alerts in protobuf format for integration with GTFS static feed. Use when you need real-time service advisories, disruptions, or alert information. |
| `BART_GET_GTFS_RT_TRIP_UPDATES` | Get GTFS-RT Trip Updates | Tool to fetch real-time trip updates in GTFS-Realtime format. Use when you need the latest live trip information as raw protobuf. |
| `BART_GET_GTFS_STATIC_SCHEDULE_FEED` | Download GTFS Static Schedule Feed | Downloads the BART static GTFS (General Transit Feed Specification) schedule feed as a ZIP archive. The GTFS feed contains comprehensive transit data including stations, routes, trip schedules, fares, and service calendars in standardized CSV format. Use this to access complete BART schedule information for route planning, analysis, or integration with transit applications. |
| `BART_BART_GET_ROUTE_INFO` | Get Route Info | Tool to fetch detailed information about a specific BART route. Use when you know the route number (1–12) or need all routes configuration. Call after confirming the route ID. |
| `BART_GET_ROUTE_SCHEDULE` | Get Route Schedule | Tool to get detailed schedule information for a specific BART route showing all trains and their stops. Use when you need to see the complete schedule for a route including departure times, station stops, bike policies, and passenger load indicators. Call this after determining the specific route number (1-12). |
| `BART_GET_SCHEDULE_ARRIVE` | Get BART Schedule Arrive | Tool to retrieve schedule information based on a specified arrival time. Use when planning trips arriving by a given time. |
| `BART_GET_SCHEDULE_DEPART` | Get BART Schedule Depart | Get BART train schedules departing from an origin station to a destination station at a specified time. Returns multiple trip options with departure/arrival times, fares (Clipper, cash, senior/disabled, youth), transfer details, train information, and platform numbers. Use this when you need to plan BART trips with specific departure times or when users ask about train schedules between two stations. |
| `BART_GET_SERVICE_ADVISORIES` | Get Service Advisories | Tool to fetch current BART service advisories. Use when you need up-to-date system-wide or station-level alerts before presenting or planning transit routes. |
| `BART_GET_STATION_ACCESS` | Get Station Access | Get comprehensive station access information including parking, transit, bike facilities, and lockers. Returns detailed access information for a specific BART station including: entering/exiting instructions, parking availability and lot capacity, bike parking and bike station details, locker availability, car-sharing options, nearby destinations, and connected transit services. Use this when you need to help users understand how to access a BART station or what facilities are available. |
| `BART_GET_STATION_INFO` | Get Station Info | Get detailed information for a specific BART station by its abbreviation code. Returns comprehensive station details including: name, location (address, city, county, coordinates), routes serving the station (northbound/southbound), platform information, nearby amenities (food, shopping, attractions), and general station description. Use this when you need detailed information about a specific BART station and you already have its 4-letter abbreviation code (e.g., 'EMBR' for Embarcadero, 'MONT' for Montgomery Street, '12TH' for 12th Street Oakland). |
| `BART_BART_GET_STATIONS` | Get BART Stations | Get a list of all BART stations with their complete information. This action retrieves information about all BART (Bay Area Rapid Transit) stations including station names, abbreviation codes, geographic coordinates (latitude/longitude), and full addresses. This is useful for finding station locations, getting station codes for other API calls, or building station lookup tools. |
| `BART_GET_STATION_SCHEDULE` | Get Station Schedule | Get detailed scheduled departure information for a specific BART station. Returns all trains departing from the station including route line, destination, departure time, bike allowance, crowding level, and platform number. Use this when you need to see all departures from a specific station. |
| `BART_GET_TRAIN_COUNT` | Get Train Count | Tool to fetch current count of trains active in the BART system. Use when you need real-time information about how many trains are currently operating. |
| `BART_LIST_ROUTES` | List BART Routes | Tool to get a list of all current BART routes/lines with basic information. Use when you need to see all available routes, their colors, directions, or route numbers. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

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- [Eventee](https://composio.dev/toolkits/eventee) - Eventee is a user-friendly event management platform for mobile and web. It boosts attendee engagement for in-person, virtual, and hybrid events.
- [Eventzilla](https://composio.dev/toolkits/eventzilla) - Eventzilla is an event management platform for creating, promoting, and running events. It streamlines ticketing, registration, and attendee coordination for organizers.
- [Humanitix](https://composio.dev/toolkits/humanitix) - Humanitix is a not-for-profit ticketing platform that donates 100% of profits to charity. It empowers event organizers to make social impact with every ticket sold.
- [Lodgify](https://composio.dev/toolkits/lodgify) - Lodgify is an all-in-one vacation rental software for property managers and owners. It centralizes bookings, guest messaging, and channel synchronization in one dashboard.
- [Planyo Online Booking](https://composio.dev/toolkits/planyo_online_booking) - Planyo Online Booking is a flexible reservation system for managing bookings by day, hour, or event. It streamlines scheduling for any business needing reservations.
- [Scheduleonce](https://composio.dev/toolkits/scheduleonce) - Scheduleonce is a scheduling platform for capturing, qualifying, and engaging with inbound leads. It streamlines appointment booking and follow-ups for faster lead conversion.
- [Supersaas](https://composio.dev/toolkits/supersaas) - Supersaas is a flexible appointment scheduling platform for businesses and individuals. It streamlines bookings, reminders, and calendar management in one place.
- [Sympla](https://composio.dev/toolkits/sympla) - Sympla is a platform for managing in-person and online events, ticket sales, and registrations. It streamlines event setup, attendee tracking, and digital content delivery.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.

## Frequently Asked Questions

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

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

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

Yes, absolutely. You can configure which Bart 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 Bart 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)