mcp-youtube-transcript
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Alternatives to mcp-youtube-transcript
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Related Servers
- AlicenseNot gradedqualityBmaintenanceEnables Claude Desktop to fetch full YouTube video transcripts from any URL, so users can summarize, translate, or cite video content without API keys or downloads.MIT
- AlicenseNot gradedqualityCmaintenanceEnables Claude AI to extract transcripts from YouTube videos with zero local setup, supporting multi-language and all URL formats.MIT
- AlicenseNot gradedqualityCmaintenanceEnables Claude AI to extract transcripts from YouTube videos with zero setup required. Works on all platforms including mobile, supports multiple languages, and handles all YouTube URL formats through a cloud-hosted service.70 npmMIT
- FlicenseAqualityDmaintenanceProvides YouTube video transcripts (text and metadata) as MCP tools for AI hosts like Claude Code, enabling summarization, search, and Q&A without watching the video.2-
- AlicenseNot gradedqualityDmaintenanceEnables AI models like Claude to easily access and utilize subtitle data from YouTube videos by extracting transcripts from video URLs with support for multiple languages.1MIT
- FlicenseNot gradedqualityCmaintenanceBrings YouTube data to Claude Code, enabling video transcripts, search, metadata, channel info, playlists, comments, trending videos, engagement analytics, chapters, SponsorBlock integration, and most-replayed heatmaps.15 npm-
TDQS
Scored across 8 tools
Multiple tools (get_youtube_transcript, get_youtube_transcript_ytdlp, get_plain_text_transcript) perform nearly identical functions, differing only in extraction method or output format. This creates significant ambiguity for an agent trying to select the right tool.
Most tools follow a get_* prefix, but the presence of list_, load_, create_, and the _v2 suffix breaks the pattern. The names are readable and descriptive, but not uniformly consistent.
8 tools is within the typical well-scoped range for a domain-specific server. However, the three transcript retrieval tools are somewhat redundant and could be consolidated without losing functionality.
The server covers the full transcript workflow: retrieval, plain text extraction, metadata, quality analysis, and resource management. Minor gaps like timestamp filtering or playlist support exist but do not break core usage.