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ManoloZocco

istat-mcp-suite

by ManoloZocco
OverviewSchemaSourceRelated ServersDiscussionsAdmin
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

    A4.1/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a distinct role: dataflow discovery, dataset constraints, concept definitions, structure diagrams, territorial code lookup, data retrieval, and cache diagnostics. Even the metadata-related tools (constraints, concepts, diagram, codes) are clearly separated by their specific inputs and outputs, so an agent should rarely confuse them.

    Naming Consistency4/5

    Most tools follow a consistent get_<noun> pattern (get_constraints, get_concepts, get_data, etc.), with one notable deviation: discover_dataflows. This is still acceptable since 'discover' conveys a search action, but it breaks the uniform get_ prefix. Overall the naming is predictable and readable.

    Tool Count5/5

    7 tools is well within the ideal range for a domain-specific server. Each tool serves a clear purpose in the workflow (discover → constrain → fetch → diagnose), and none are redundant or unnecessary. The count feels intentionally scoped.

    Completeness4/5

    The core workflow of discovering datasets, retrieving their constraints, and fetching data is fully covered. Supporting tools for semantic concepts, territorial codes, structure visualization, and cache diagnostics fill out the domain nicely. Minor gaps include an inability to list all dataflows without a keyword and no explicit way to get raw dataflow metadata beyond constraints, but these are workarounds rather than dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources