Query Google Maps for Indian Business Data

A Python-based MCP server that wraps the Google Maps and Places APIs to answer natural-language queries about local businesses and tourist attractions in India - questions like "What are the best cafes in Bangalore?" or "Top-rated tourist places near Hyderabad" - through a simple MCP interface.

Use this when an LLM client needs to query Google Maps/Places data for businesses, restaurants, or tourist attractions, particularly for India-focused local search. It requires bringing your own Google Maps API key and is scoped to place, business, and attraction lookups rather than full mapping features like routing or turn-by-turn directions.

• Query Google Maps for places, restaurants, tourist attractions, and more.
• Configurable with your own Google Maps API key.
• Modular, maintainable, testable codebase, built to be extended and contributed to.

Requires Python 3.8+ and a Google Maps API key. Install uvx with curl -LsSf https://astral.sh/uv/install.sh | sh, then run the server with uvx google-mcp-server. Building from a cloned repo: run uv build from the project root, set GOOGLE_MAPS_API_KEY in your environment (e.g. export GOOGLE_MAPS_API_KEY=your_api_key_here), ensure ~/.local/bin is on your PATH, then run the built wheel with uvx dist/google_maps_mcp-1.0.0-py3-none-any.whl. For VS Code, configure it as a stdio server:

"mcp": {
        "servers": {
            "google_maps_mcp_server":{
                "type": "stdio",
                "command": "uvx",
                "args": ["google-maps-mcp"],
                "env": {
                    "GOOGLE_MAPS_API_KEY": "<your google maps API key>"
                }
            }
        }
    }

Developers building India-focused local-search or travel assistants who want Google Maps/Places business and attraction data available directly to an MCP-compatible LLM client, without writing their own Google Maps API wrapper. The project also welcomes contributions - forking the repo, adding tests, and submitting a pull request with a clear description of the change - since it's explicitly built to be modular and extended over time.