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How to integrate Bart MCP with Mastra AI

Connect Mastra AI to Bart MCP. Find next departures from embarcadero station, get real-time trip updates for richmond line, and more using natural language, with authentication handled for you.

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Bart is the Bay Area Rapid Transit system, providing fast public transportation across the San Francisco Bay Area. It helps commuters and travelers get real-time schedule info, plan routes, and stay updated on service changes.

18 Tools

Introduction

This guide walks you through connecting Bart to Mastra AI using the Composio tool router. By the end, you'll have a working Bart agent that can check real-time departures, plan trips with arrival and departure schedules, look up fares, view service advisories, and check elevator status through natural language commands.

This guide will help you understand how to give your Mastra AI 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

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TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Bart tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Bart tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Bart agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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 your Bart account. It provides structured and secure access to BART schedules, fares, routes, stations, and live service information, so your agent can check departures, plan trips, compare fares, monitor advisories, and review station access on your behalf.

  • Real time departure tracking: Have your agent check estimated departures from a chosen BART station and report how many trains are currently active.
  • Trip schedules and fares: Let the agent find scheduled trips by departure or arrival time and compare Clipper and cash fares between stations.
  • Routes and station details: Direct your agent to list BART routes, inspect route schedules, and retrieve detailed station information.
  • Service and elevator updates: Instruct your agent to check current service advisories, trip updates, and elevator status across BART stations.
  • Station access planning: Have your agent review parking, connecting transit, bike facilities, and locker options before your trip.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Bart through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Bart

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["bart"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Bart MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "bart" for Bart access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Bart toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "bart-mastra-agent",
    instructions: "You are an AI agent with Bart tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

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

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        bart: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Bart toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Bart and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["bart"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      bart: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "bart-mastra-agent",
    instructions: "You are an AI agent with Bart tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { bart: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Bart through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows
TOOLS

Supported Tools

Every Bart action and event your agent gets out of the box.

Get BART API Version

Get the current version of the BART API.

Get Elevator Status

Tool to fetch current elevator status across all BART stations.

Get Estimated Departures

Tool to get real-time estimated departure times for a specified BART station.

Get BART Fare

Get fare information between two BART stations including Clipper and cash prices.

Get GTFS-RT Service Alerts

Fetch BART GTFS-RT service alerts as protobuf bytes for use with the static GTFS feed.

Get GTFS-RT Trip Updates

Fetch BART GTFS-Realtime trip updates as raw protobuf bytes.

Download GTFS Static Schedule Feed

Fetch the BART static GTFS schedule feed ZIP and return its permalink and the first 1,024 bytes of its content.

Get Route Info

Tool to fetch detailed information about a specific BART route.

Get Route Schedule

Tool to get detailed schedule information for a specific BART route showing all trains and their stops.

Get BART Schedule Arrive

Tool to retrieve schedule information based on a specified arrival time.

Get BART Schedule Depart

Get BART train schedules departing from an origin station to a destination station at a specified time.

Get Service Advisories

Tool to fetch current BART service advisories.

Get Station Access

Get comprehensive station access information including parking, transit, bike facilities, and lockers.

Get Station Info

Get detailed information for a specific BART station by its abbreviation code.

Get BART Stations

Get a list of BART stations with names, abbreviation codes, geographic coordinates, and addresses.

Get Station Schedule

Get detailed scheduled departure information for a specific BART station.

Get Train Count

Tool to fetch current count of trains active in the BART system.

List BART Routes

List BART routes with basic information such as colors, directions, and route numbers.

FRAMEWORKS

How to build Bart MCP Agent with another framework

Claude Code logo

Claude Code

Use Bart MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Bart MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Bart MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Bart MCP with Claude Agent SDK

Codex logo

Codex

Use Bart MCP with Codex

OpenClaw logo

OpenClaw

Use Bart MCP with OpenClaw

Hermes logo

Hermes

Use Bart MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Bart MCP with Atomic Agent

Google ADK logo

Google ADK

Use Bart MCP with Google ADK

LangChain logo

LangChain

Use Bart MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Bart MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Bart MCP with LlamaIndex

CrewAI logo

CrewAI

Use Bart MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Bart MCP with Pydantic AI

AutoGen logo

AutoGen

Use Bart MCP with AutoGen

FAQ

Frequently asked questions

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.

Yes, you can. Mastra AI 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.

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.

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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