YouTube Audio & Transcript MCP Server
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AlicenseAqualityBmaintenanceEnables AI agents to retrieve YouTube transcripts from individual videos, channels, and search results, supporting multiple output formats such as plain text, SRT, and VTT.37 npmMIT- AlicenseAqualityCmaintenanceEnables MCP clients and agents to fetch YouTube transcripts and caption lists from video IDs or links, preferring manual/auto captions by ordered language preference and falling back to local Faster-Whisper audio transcription when captions are unavailable. Results include source, language, full text and timestamped segments, with CLI exports to JSON, text, SRT and WebVTT, all without paid APIs or API keys.3MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to extract YouTube video metadata and generate high-quality multilingual transcriptions with voice activity detection, supporting 99 languages with translation capabilities and intelligent caching.56MIT
- AlicenseAqualityFmaintenanceEnables AI agents to download, transcribe, and inspect video or audio URLs from YouTube, TikTok, X, and 1000+ other sites using server-side yt-dlp, residential proxies, and speech-to-text.912 npmMIT
- AlicenseAqualityDmaintenanceEnables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.914 npm59Apache 2.0
- AlicenseAqualityCmaintenanceExtract YouTube transcripts for AI agents, RAG pipelines, and LLM workflows. Supports any YouTube URL. Returns clean text or timestamped segments. No API keys required.14MIT
TDQS
Scored across 3 tools
Each tool targets a clearly distinct action: youtube_to_audio produces audio files, youtube_transcript retrieves captions, and get_job polls async jobs from either. There is no realistic overlap that would cause misselection.
The three names use three different patterns: youtube_to_audio (noun_to_noun with verb), youtube_transcript (noun_noun, no verb), and get_job (verb_noun). All are snake_case and readable, but the convention is mixed rather than predictable.
Three tools is lean but each earns its place: two capabilities plus the shared async-job poller. It is slightly minimal (no batch/playlist helper), but well-scoped for the server's narrow purpose.
The core surface (audio extraction, transcript retrieval, and job-status handling for both async flows) is fully covered with no dead ends. Minor gaps exist: no playlist/batch support and no lightweight video metadata lookup.