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Hugging Face Hub MCP Server

Hugging Face Hub MCP Server

by michaelwaves

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Alternatives to Hugging Face Hub MCP Server

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to search and inspect Hugging Face models, datasets, spaces, papers, and documentation, including repository details, file listings, and documentation search/fetch. Runs keyless by default, with optional token support for identity checks, higher rate limits, and private or gated content.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Search and retrieve models, datasets, and spaces from Hugging Face Hub. Enables browsing trending items and getting detailed info on repos.
      565 npm
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables agents to trace any Hugging Face model's ancestry and descendants, find the most finetuned base models, and explore whole model families. It exposes tools for lineage, children, leaderboards, family views, and model search, answering from nightly-rebuilt index data.
      2
      6
      19
      MIT

    TDQS

    A3.6/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: there are separate tools for datasets vs. models, and within each category, tools for getting info, listing all, getting tags, and dataset-specific tools for Croissant metadata and parquet files. The descriptions make the boundaries explicit, preventing misselection.

    Naming Consistency5/5

    All tools follow a consistent 'hf_' prefix with verb_noun pattern (e.g., hf_get_dataset_info, hf_list_models). The naming is uniform across the set, using snake_case and clear verbs like 'get', 'list', and 'get' for specific actions, making it predictable and readable.

    Tool Count5/5

    With 8 tools, this server is well-scoped for interacting with the Hugging Face Hub. It covers core operations for datasets and models (info, listing, tags) plus dataset-specific features like Croissant and parquet files, avoiding bloat while providing essential functionality.

    Completeness4/5

    The tool set covers read operations comprehensively for datasets and models, including metadata, listings, tags, and file access. A minor gap is the lack of write operations (e.g., upload or modify datasets/models), but for a read-focused server, it handles the domain well with no dead ends.