Tomtom Maps MCP, developed by Tomtom International, is an integration server designed to connect Model Context Protocol (MCP)-enabled AI applications with TomTom's location services. Built primarily with Node.js, TypeScript, and JavaScript, it offers both a hosted remote service and a local server option via its GitHub repository. This platform allows AI agents to access essential mapping, routing, and geocoding capabilities, enriching AI workflows with real-world spatial intelligence. It functions as a key component for developers building location-aware AI solutions across various industries.

What does Tomtom Maps MCP connect to?

The Tomtom Maps MCP Server links AI applications to TomTom's extensive location services. This includes advanced routing algorithms for efficient pathfinding, detailed map display for visualization, real-time traffic data for dynamic adjustments, and global search and geocoding capabilities for precise location identification. As an MCP server, it enables AI applications to directly interact with TomTom's data and APIs, providing essential spatial context. This integration supports diverse AI-driven tasks requiring geographic information.

Core features and tools

Tomtom Maps MCP exposes a collection of callable tools for AI applications. These include tomtom-geocode, tomtom-reverse-geocode, tomtom-fuzzy-search, tomtom-poi-search, tomtom-nearby, tomtom-routing, tomtom-waypoint-routing, tomtom-reachable-range, tomtom-traffic, tomtom-static-map, and tomtom-dynamic-map. When utilizing the Public Preview Orbis backend, additional tools become available: tomtom-ev-routing, tomtom-search-along-route, tomtom-area-search, tomtom-ev-search, and tomtom-data-viz. Note that tomtom-static-map is exclusive to the default TomTom Maps backend.

Who is it for?

Tomtom Maps MCP is for developers creating AI agents and applications that require location intelligence. This includes professionals in automotive, geomarketing, retail, urban planning, and logistics sectors. It serves those needing to embed mapping, routing, and search functionalities into their AI solutions. This is not the right fit if your AI application does not require external location data or mapping services.

How to get started

The server authenticates using an API key passed as an HTTP header or environment variable. This setup involves configuring the AI client to connect to the MCP server's HTTP endpoint.

Use cases

• Route Planning Assistant: Find the fastest route between locations, avoid specific road types, and identify points of interest along the way.
• Location Intelligence: Convert coordinates to addresses using reverse geocoding and search for nearby services or points of interest within a specified radius.
• Traffic-Aware Route Planning: Plan routes that account for current traffic conditions and suggest alternative routes in case of delays.

Tomtom Maps MCP provides AI applications with essential location intelligence through its Model Context Protocol integration. It enables developers to incorporate advanced mapping, routing, and search capabilities into their AI agents. Supporting various AI clients and models, it extends the reach of AI into real-world geographic contexts for diverse industry needs.