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mcp-altair-studio

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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

    A3.7/5.0

    Scored across 18 tools

    Disambiguation5/5

    Each tool targets a distinct data science operation or utility (e.g., classification vs. clustering vs. PCA vs. data cleaning), with no overlapping responsibilities. The advanced escape hatch is clearly separated as a catch-all for unsupported operators.

    Naming Consistency5/5

    All tools follow a consistent 'altair_verb_noun' pattern in snake_case, with clear action words (e.g., import_data, train_classifier, run_operator_chain). The minor deviation in 'descriptive_stats' still fits the pattern well.

    Tool Count5/5

    18 tools is well-calibrated for a data science MCP server, covering data ingestion, preparation, modeling, evaluation, and process management without being overwhelming. Each tool feels necessary and justified.

    Completeness4/5

    The set covers the core data science workflow (import, clean, transform, model, evaluate, export) thoroughly. A dedicated regression tool is missing, but the advanced operator-chain escape hatch fills that gap, making it nearly complete for common tasks.

    Maintenance

    ActivityStale
    ResponsivenessNo issues

    Resources