by google
Find official MCP servers for Google Maps. Explore resources to build, integrate, and extend apps with Google directions
Connects Google Maps Platform APIs to AI models through MCP, enabling natural language queries for places, routes, elevation data, and weather with 3D map visualization.
Google Maps is an official MCP server published by google that provides AI assistants with tools and capabilities via the Model Context Protocol. Find official MCP servers for Google Maps. Explore resources to build, integrate, and extend apps with Google directions It is categorized under cloud infrastructure, developer tools.
You can install Google Maps in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
Apache-2.0
Google Maps is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Google Maps against two servers with overlapping tools; this profile had the clearer scope statement.
Google Maps is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Google Maps has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Google Maps benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired Google Maps into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated Google Maps against two servers with overlapping tools; this profile had the clearer scope statement.
We wired Google Maps into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Google Maps benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Google Maps has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Google Maps is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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Find official MCP servers for Google Maps. Explore resources to build, integrate, and extend apps with Google directions
TL;DR: Connects Google Maps Platform APIs to AI models through MCP, enabling natural language queries for places, routes, elevation data, and weather with 3D map visualization.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
