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geospatial-mcp

by ystoneman
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Python
Hybrid

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      Apache 2.0
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.2/5.0

    Scored across 22 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: coordinate validation/conversion/CRS transformation, geometry operations, place lookup, routing modes, terrain, weather, time, data conversion, and RF analysis are all separated. Descriptions explicitly cross-reference similar tools (e.g., coord_convert vs coord_transform_crs, geom_measure vs route_directions), so misselection is unlikely.

    Naming Consistency4/5

    Tool names follow a predictable lower_snake_case prefix-based pattern (coord_, geom_, place_, route_, terrain_, rf_) and are readable. However, not all follow a single verb_noun grammar: some are noun_noun (route_directions, env_weather) or noun_prep_noun (time_at_location), making the convention consistent but not perfectly uniform.

    Tool Count4/5

    At 22 tools, the count sits above the typical 3-15 range and feels slightly heavy, but the broad geospatial domain justifies the number. Each tool covers a distinct capability with no obvious redundancy, and the prefix grouping keeps the set navigable.

    Completeness4/5

    The tool surface covers core geospatial workflows well: coordinate/CRS handling, geometry analysis, geocoding/search, routing, terrain, weather, timezone, data conversion, and RF. Minor gaps such as batch geocoding, historical weather, or route optimization exist, but most are workarounds and tools compose cleanly (e.g., isochrones into geom_overlay/relate).

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources