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bilinote-mcp

by caiqianzhang
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Python
Remote

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    • Bilibili API MCP Server

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      F
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      quality
      D
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      Enables interaction with Bilibili (哔哩哔哩) through its API, supporting video search and recommendations, user search, dynamic feeds, video collections, and danmaku retrieval through natural language.
      5
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    • bilibili-mcp

      sandraschi
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      A
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      B
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      Enables agents to search, explore trending content, retrieve video metadata and hot comments, and obtain subtitle transcripts for summarisation on Bilibili, with an anonymous tier and an optional account tier for personalized feeds.
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    • bili-note-mcp

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      A
      license
      Not graded
      quality
      C
      maintenance
      Enables agents to turn Bilibili course videos into structured VitePress study notes by extracting subtitles, generating organized notes with key points and active recall, and saving them locally. It also supports video search and metadata retrieval through MCP tools.
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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 15 tools

    Disambiguation5/5

    Each tool targets a distinct resource/action: search, video info, subtitles, chapters, audio download, ASR, comments, uploader/collection/favorite listing, and QR login. Even the subtitle-related tools are clearly separated by existing vs generated transcripts and single vs batch operations, with explicit cross-references.

    Naming Consistency4/5

    Most tools follow a predictable verb_noun pattern with consistent list_favorite_ and list_uploader_ prefixes. Minor deviations like asr_transcribe and get_collection_videos (instead of list_collection_videos) break the pattern slightly, but the overall style remains readable and navigable.

    Tool Count5/5

    With 15 tools, the server sits at the upper edge of the ideal range, and each tool maps to a concrete step in the video-to-notes workflow. There are no redundant or decorative tools, and the breadth is justified by the many ways Bilibili content can be discovered and collected.

    Completeness5/5

    The tool surface covers the full pipeline: search/discovery, video and chapter metadata, transcript acquisition via existing subtitles or ASR, comment context, batch collection/favorite workflows, and login support. Missing write operations are irrelevant for a read/extract server, so agents have no dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources