YouTube Transcript MCP
Related Servers
Alternatives to YouTube Transcript MCP
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Related Servers
- AlicenseAqualityBmaintenanceEnables MCP-aware agents to fetch direct captions or download audio and transcribe with local Whisper from common video platforms like YouTube, Vimeo, and Twitch.91MIT
- AlicenseNot gradedqualityCmaintenanceEnables MCP-compatible assistants to retrieve caption text from YouTube videos as either plain text or timestamped snippets for reading, summarizing, or searching. Supports local stdio and stateless HTTP deployments for integration with Claude Desktop, Claude Code, Cursor, and similar clients.MIT
- AlicenseAqualityAmaintenanceMCP server that fetches YouTube video transcripts and optionally summarizes them. Supports multiple transcript formats (text, JSON, SRT, WebVTT), multi-language retrieval, and flexible YouTube URL parsing.658 PyPI6MIT
- AlicenseNot gradedqualityBmaintenanceFetches YouTube video transcripts with timestamps and provides them to LLM agents via MCP, enabling natural language access to video content.69 npm4MIT
- FlicenseNot gradedqualityDmaintenanceMCP server providing tools to fetch YouTube video transcripts with metadata, supporting direct YouTube transcripts and audio transcription via multiple backends (whisper, AssemblyAI, OpenAI, Gemini).-
- AlicenseAqualityDmaintenanceEnables users to extract, search, and analyze YouTube video transcripts directly within MCP-compatible clients. It supports advanced features like time-chunked summaries, keyword searching with surrounding context, and batch processing for multiple videos.4MIT
TDQS
Scored across 3 tools
Each tool targets a distinct action: get_transcript fetches transcript content, list_captions enumerates available caption tracks, and get_status reports local capabilities. There is no overlap in purpose, and the descriptions clearly delimit when to use each.
All three tools follow a strict verb_noun convention (get_transcript, list_captions, get_status). The pattern is predictable and immediately readable.
Three tools is a tight, well-scoped set for a narrow transcript-retrieval domain, with each tool earning its place. It is on the lean side, but nothing feels missing or redundant.
The surface covers the core lifecycle: discover captions, fetch transcript, and check capabilities/limits. Minor gaps like batch fetching or in-transcript search are outside the stated purpose and easily worked around.