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Alternatives to kaggle-mcp

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    Related Servers

    • A
      license
      B
      quality
      A
      maintenance
      A local stdio MCP server that gives Claude on-demand access to any Kaggle competition's brief, rules, evaluation, data description, leaderboard, top discussions and public notebooks, using the user's own Kaggle credentials and a disk cache with no hosted infrastructure. It also exposes a live tool for spotting forum topics and comments posted since the last fetch.
      4
      10
      2
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Connects Claude AI to the Kaggle API through the Model Context Protocol, enabling users to browse competitions, search and download datasets, analyze kernels, and access pre-trained models through natural language interactions.
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Connects Claude AI to the Kaggle API through the Model Context Protocol, enabling competition, dataset, and kernel operations through the AI interface.
      35
      MIT

    TDQS

    A3.7/5.0

    Scored across 41 tools

    Disambiguation5/5

    Each tool targets a distinct resource or action, with detailed descriptions that clearly differentiate them. For example, kaggle_get_competition, kaggle_competition_landscape, and kaggle_competition_leaderboard serve different purposes (details, triage, leaderboard). There is no ambiguity.

    Naming Consistency4/5

    All tools share the kaggle_ prefix and use underscore-separated names. Most follow a verb_noun pattern (e.g., kaggle_get_competition, kaggle_list_datasets), but some are noun-first (e.g., kaggle_competition_landscape, kaggle_competition_leaderboard). This minor inconsistency does not hinder readability.

    Tool Count3/5

    With 41 tools, the server covers a broad Kaggle domain (competitions, datasets, kernels, discussions, models). While each tool has a clear purpose, the count is at the high end considering the scope. A more streamlined set could reduce cognitive load.

    Completeness5/5

    The tool surface is remarkably complete for Kaggle workflows, covering competition lifecycle (list, get, download, EDA, submit, track), dataset management (search, create, version, delete), kernels (push/pull/status/output), discussions (search/get), models (list/download/delete), and admin (auth, audit, status). Obvious gaps like discussion posting are due to API limitations.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues