Stadia Maps MCP Server
Location APIs for AI Agents
Effortlessly integrate real-time geospatial data into your AI workflows and agents. Enhance context, improve accuracy, and accelerate AI development with Stadia Maps' robust location platform.
Enhance AI Agents with Real-World Location Intelligence
Seamlessly embed maps, geocoding, routing, and geospatial context into AI tooling and agent workflows.
Stadia Maps' Model Context Protocol (MCP) server provides real-time, accurate location data directly to your AI stack—ensuring your agents understand the world, not just the text.
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Stadia Maps MCP Server for self-hosting
Explore the GitHub repo for quickstart guides, examples, and detailed documentation. It's easy to get started!
Fully-Hosted Location API MCP Server
Professional plan subscribers will soon access a fully hosted server option, allowing you to focus purely on AI development without infrastructure concerns.
Location-Powered AI: Why It Matters
- Geospatial Context at Scale: Equip agents with up-to-date maps, routing, time zones, and place info, enabling accurate responses to location-based queries.
- Smart Interactions: Directly utilize geocoding, routing, isochrones, static map generation, and place search within your AI workflows.
- TypeScript First: Fully typed, modular SDK in TypeScript—choose exactly the tools your agents require.
Out-of-the-Box Location Tools
A complete suite of ready-to-integrate services
- Time & Time Zones – Accurate current time, UTC offset, DST status.
- Geocoding & Place Search – Address lookup, POIs, and autocomplete.
- Routing & Travel Time – Precise directions, travel matrices, and isochrones.
- Map Imagery – Generate static maps, overlay routes, and place markers.
Developer-Centric Integration
- Plug + Play: Quickly integrate by cloning the repository, adding your Stadia Maps API key, and installing dependencies.
- LLM-Ready Examples: Demonstrations for Anthropic/Claude integration.
- Modular Prompt & Tool Architecture: Tailor tools specifically for your AI flows, minimizing unnecessary context.