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Development Indicators MCP

by lbruce-wq
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Python
Hybrid

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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

    A3.5/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool has a distinct purpose: listing sources, retrieving setup details, finding microdata, searching indicators, FAOSTAT-specific queries, geography resolution, metadata retrieval, observation retrieval, and comparison. Descriptions clearly differentiate overlapping areas like list_sources vs find_microdata.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern (e.g., list_sources, get_observations, compare_observations). Prefixing FAOSTAT-specific tools with 'faostat_' adds a clear namespace without breaking the pattern.

    Tool Count5/5

    With 10 tools, the server is well-scoped for discovering, searching, and retrieving development indicator data. This count is within the ideal range and each tool earns its place by covering a distinct part of the workflow.

    Completeness4/5

    The surface covers the full discovery-to-retrieval pipeline: source enumeration, search, metadata, observations, and comparison. Minor gaps exist (e.g., no bulk download or time-series filtering), but these are not severe dead ends for typical use cases.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources