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youtube-context-mcp

by realiti4
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Python
Remote

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    • yt

      progrmoiz
      A
      license
      Not graded
      quality
      Not graded
      maintenance
      An MCP server that provides YouTube data access without API keys or quotas. It enables agents to search videos, retrieve transcripts and metadata, and perform full-text search across cached content for AI context retrieval.
      3 npm
      -

    • yt-mem-ai

      dasein108
      A
      license
      Not graded
      quality
      B
      maintenance
      An MCP server that gives AI assistants a local YouTube memory: transcribe videos, store and search transcripts, follow subscriptions, and generate summaries, timestamped highlights, and digests, all on your machine with no cloud or API keys.
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    • tldw-mcp

      limace11
      A
      license
      Not graded
      quality
      D
      maintenance
      MCP server that extracts YouTube video transcripts (including metadata) as Markdown, enabling AI to summarize and discuss video content without watching it.
      MIT
    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

    A4.6/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool targets a clearly distinct concern: transcript retrieval, transcript listing, metadata, replayed peaks, a single frame, a preview sheet, and link building. Even the two visual tools are unambiguous because one captures one moment while the other makes a timeline overview.

    Naming Consistency4/5

    The naming is mostly predictable with get_ for retrieval, list_ for enumeration, and build_ for the link helper. The slight inconsistency is that build_video_link breaks the get_/list_ pattern, but it is still a sensible verb for its purpose.

    Tool Count5/5

    Seven tools is well-scoped for a YouTube context server. Each tool covers a distinct aspect of getting information from a video, and none feel redundant or unnecessary.

    Completeness5/5

    The surface covers the core needs for answering questions about a YouTube video: textual transcript, available languages, metadata, engagement peaks, and visual context. There are no obvious dead ends; visual tools complement transcript and metadata tools well.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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