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YouTube MCP Server

YouTube MCP Server

by granitebps
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TypeScript
Hybrid

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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
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    • tube-bridge

      TheWhiteWater
      A
      license
      A
      quality
      B
      maintenance
      A YouTube MCP server that enables AI agents to search videos, fetch transcripts, comments, and channel info, with optional API key for extra features and local semantic search via corpora.
      17
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    • YouTube Toolbox

      jikime
      A
      license
      B
      quality
      D
      maintenance
      An MCP server that provides AI assistants with powerful tools to interact with YouTube, including video searching, transcript extraction, comment retrieval, and more.
      8
      19
      Apache 2.0
    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

    A4.1/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool targets a clearly distinct resource and action: video metadata, comments, transcript content, language discovery, search, and server info. There is no overlap in purpose, and the transcript/language split is explicitly signposted (call get_transcript_languages first).

    Naming Consistency4/5

    Most tools follow a get_<resource> pattern (get_video_info, get_video_comments, get_video_transcript, get_server_info), which is highly readable. Minor deviations exist: search_youtube uses a different verb form and get_transcript_languages breaks the get_video_ prefix used by its sibling transcript tool.

    Tool Count5/5

    Six tools is well-scoped for a read-oriented YouTube data server, with each tool earning its place and no redundant operations. It sits comfortably in the ideal 3-15 range.

    Completeness4/5

    The surface covers the core read workflows well: video metadata, comments, transcripts, language discovery, and search. Gaps exist around channel-level and playlist operations, but these are workable omissions for a video-centric read-only server.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources