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stevenyuser

NBA MCP Server

by stevenyuser
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Python

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    TDQS

    A3.6/5.0

    Scored across 10 tools

    Disambiguation5/5

    Every tool has a clearly distinct purpose targeting specific resources (league standings, live games, players, teams, scoreboard) with no overlap. The descriptions clearly differentiate between standings, boxscores, play-by-play, awards, stats, logs, details, and scoreboard data, making misselection unlikely.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with 'get_' prefix, followed by the resource type (e.g., league_team_standings, player_awards, team_details). The naming is uniform throughout, using snake_case consistently without any deviations or mixed conventions.

    Tool Count5/5

    With 10 tools, the count is well-scoped for an NBA data server, covering core areas like standings, live games, players, teams, and scoreboard. Each tool earns its place by providing distinct data retrieval functions without being overly sparse or bloated.

    Completeness4/5

    The toolset provides comprehensive coverage for retrieving NBA data, including CRUD-like operations for players and teams (e.g., stats, logs, details) and live game information. A minor gap exists in the lack of tools for creating or updating data (e.g., posting comments or simulations), but this is reasonable for a read-only data server focused on retrieval.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources