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Alternatives to sat-score-percentiles-mcp

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    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to query official Census Bureau statistics and metadata, including dataset listings, geography levels, aggregate data, and FIPS code resolution. It also provides prompts for retrieving population data for states, counties, cities, and other geographic areas.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Connects AI assistants with official U.S. Census Bureau statistics, enabling them to discover available datasets, resolve place names to FIPS geography codes, and retrieve aggregate demographic and economic data through natural language. It draws on both the live Census Data API and a locally seeded database for faster search.
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Connects AI assistants with official Census Bureau data sources, letting them list datasets, resolve place names to FIPS codes, and pull aggregate statistics for states, counties, cities, and other geographies. Queries are served from the Census Data API with a local Postgres mirror for faster, more robust search.
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to access official Census Bureau statistics by listing datasets, fetching aggregate data and geography, resolving FIPS codes, and retrieving population data through natural-language prompts.
      -

    TDQS

    A3.9/5.0

    Scored across 4 tools

    Disambiguation4/5

    The four tools target distinct operations: score→percentile, percentile→score, state lookup, and state ranking. The only risk is the near-mirror pair get_sat_percentile vs get_score_for_sat_percentile, which are inverse functions with very similar names; the descriptions disambiguate direction, but an agent could still pick the wrong one at a glance.

    Naming Consistency4/5

    All names are snake_case with verb-first phrasing (get_*, rank_*), which is consistent and readable. The minor deviation is that the two inverse tools use asymmetric, easily-confused constructions rather than a clean pattern like percentile_for_score / score_for_percentile.

    Tool Count5/5

    Four tightly scoped tools map exactly onto the domain's two axes (score↔percentile conversion and state-level data/ranking). Each tool earns its place with no redundancy or filler.

    Completeness4/5

    Both directions of percentile lookup plus state detail and cross-state ranking give solid coverage. Minor gaps remain: no tool to compare two scores or list available states/metrics, and no national-aggregate lookup beyond what's embedded in the state comparison.