How to integrate Tomtom MCP with Mastra AI

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Introduction

This guide walks you through connecting Tomtom to Mastra AI using the Composio tool router. By the end, you'll have a working Tomtom agent that can find nearby ev charging stations with live status, calculate fastest driving route to airport, search for italian restaurants around times square, get current traffic speed on main street through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Tomtom account through Composio's Tomtom MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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 Tomtom tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Tomtom 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 Tomtom 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 Tomtom MCP server, and what's possible with it?

The Tomtom MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Tomtom account. It provides structured and secure access to TomTom's advanced mapping, navigation, and location services, so your agent can perform actions like calculating routes, searching for points of interest, retrieving live traffic data, and managing map assets on your behalf.

  • Dynamic route calculation and navigation: Ask your agent to generate driving, walking, or cycling routes with waypoints and real-time traffic considerations to optimize travel plans.
  • Flexible location and place search: Let your agent perform fuzzy searches for addresses or points of interest, or find nearby locations by category such as restaurants, EV charging stations, or landmarks.
  • Real-time traffic flow and road insights: Retrieve up-to-date traffic flow data for specific road segments, helping you monitor congestion, speed trends, and plan detours proactively.
  • EV charging station availability: Check the current status and availability of EV charging stations, making it easy to plan electric vehicle journeys with confidence.
  • Map styling and asset management: Manage map fonts, styles, sprites, and copyrights to customize the look and feel of maps integrated into your applications.

Supported Tools & Triggers

Tools
List Map FontsTool to list available font asset versions for map rendering.
List Assets SpritesTool to list available sprites for a given asset version.
List map stylesTool to list available map styles.
Calculate RouteTool to calculate driving routes.
Category SearchTool to search for points of interest by category.
EV Charging Stations AvailabilityTool to retrieve ev charging station availability info.
Flow Segment DataTool to retrieve traffic flow data for a specific road segment.
Fuzzy SearchTool to perform a fuzzy search for addresses and points of interest.
List Sprite VersionsTool to list available sprite asset versions.
Get Map CopyrightsTool to retrieve copyright information for a specific map tile.
MAP_DISPLAY_RASTER_TILETool to retrieve a raster map tile for specified coordinates and zoom.
Map Display Static ImageTool to fetch a static map snapshot given center coords and zoom.
Map Display WMS GetMapTool to retrieve a map image via wms getmap.
Matrix RoutingTool to calculate travel time and distance matrix between multiple locations.
Nearby SearchTool to find points of interest near a specified location.
Points of Interest SearchTool to search for points of interest by query.
Reverse GeocodeTool to convert geographic coordinates into a human-readable address.
Structured GeocodeTool to convert structured address fields into coordinates.
Traffic IncidentsTool to retrieve detailed traffic incidents within a bounding box.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

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

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 Tomtom through MCP.

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

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

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

Create a Tool Router session for Tomtom

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

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

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 Tomtom toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "tomtom-mastra-agent",
    instructions: "You are an AI agent with Tomtom 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

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: {
        tomtom: 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 Tomtom 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 Tomtom 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: ["tomtom"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "tomtom-mastra-agent",
    instructions: "You are an AI agent with Tomtom 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: { tomtom: 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 Tomtom 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

How to build Tomtom MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Tomtom MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Tomtom MCP with Claude Agent SDK

Google ADK

Google ADK

Use Tomtom MCP with Google ADK

LangChain

LangChain

Use Tomtom MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Tomtom MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Tomtom MCP with LlamaIndex

CrewAI

CrewAI

Use Tomtom MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Tomtom MCP?

With a standalone Tomtom MCP server, the agents and LLMs can only access a fixed set of Tomtom tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Tomtom and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Mastra AI?

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 Tomtom tools.

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

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

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