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Charlotte-Mecklenburg MCP Server

by Lavoiedavidw

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    TDQS

    A4.3/5.0

    Scored across 21 tools

    Disambiguation4/5

    Most tools target distinct datasets (parcels, zoning, crime, planning, transportation), but the crime tools (crime_near, violent_crime_near, homicides_near) and planning tools (area_plans_at, get_planning_area) overlap in purpose and could cause misselection. Descriptions are detailed enough to resolve ambiguity.

    Naming Consistency4/5

    Names mostly follow a predictable pattern: [subject]_near for radius searches, [subject]_at for point-in-polygon lookups, and verb_noun (get_, lookup_, search_) for direct lookups. Minor deviations exist (geocode, get_planning_area vs area_plans_at) but the mixed conventions are still readable and consistent within their categories.

    Tool Count4/5

    21 tools is slightly heavy but justified by the wide scope of municipal data (geocoding, parcels, zoning, crime, transit, environment). Each tool covers a distinct dataset, so the count feels appropriate for the server's purpose.

    Completeness4/5

    The tool surface covers a broad range of civic data with read-only queries, and list_datasets helps discover additional layers. Minor gaps exist (e.g., no generic query tool for arbitrary layers, no parks or building permits) but agents can work around these for most core workflows.

    Maintenance

    ActivityStale
    ResponsivenessNo issues