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geoparquet-mcp

by rteina
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Python
Remote

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    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

    A4.9/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct analytical task: metadata inspection, row preview, spatial feature extraction, nearest-neighbor search, grouped aggregation, H3 density binning, polygon containment counting, and ad-hoc SQL. The spatial/counting tools overlap thematically, but their usage guidance clearly separates feature retrieval from counting, ranking, and binning.

    Naming Consistency4/5

    All tools share the geoparquet_ prefix and lowercase snake_case convention, and nearly all follow a verb-first pattern. A few names like filter_spatial, find_nearest, and count_in_polygons use adjectival or prepositional objects rather than strict verb_noun, which is a minor deviation from the otherwise consistent style.

    Tool Count5/5

    Eight tools is well within the ideal range and each tool earns its place by covering a distinct query shape or analysis workflow. There is no bloat or redundancy; the set feels deliberately scoped for efficient remote GeoParquet querying.

    Completeness5/5

    The tool surface covers the full read-only analytical lifecycle: inspect schema, preview values, filter spatially, find nearest features, aggregate attributes, summarize by H3 cell, count points in polygons, and run arbitrary read-only SQL for anything outside the typed tools. The run_sql escape hatch and polygon-count join close the obvious gaps an agent might encounter.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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