Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.
A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to GIS operations using GIS libraries, enabling AI assistants to perform accurate geospatial operations and transformations.
Google Maps MCP server with 8 tools (geocode, search, directions, elevation), stdio + StreamableHTTP transport, Agent Skill definitions, and standalone exec CLI mode.
Quality signal
48/100 (Fair)
49/100 (Fair)
Install path
pip · high
npx · high
Engagement
0 0 0 176
2 0 0 413
Tools
Supports multiple GIS data sources (climate, biodiversity, land cover, etc.)Provides geospatial operations and transformations via GIS librariesInstallation available through DockerSupports HTTP and stdio transport protocolsStorage options include local filesystem and GCP Cloud Storage
18 tools including geocode, directions, elevation, weather, air quality, and static mapsComposite tools for exploring areas, planning routes, comparing places, and local rank trackingSupports stdio, StreamableHTTP, and standalone CLI execution modesAgent Skill definitions for chaining geospatial tool callsSelf-hosted with MIT license and requires Google Places and Routes APIs enabledBatch geocoding and distance matrix calculations with advanced filtering options