YouTube MCP Server
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Alternatives to YouTube MCP Server
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Related Servers
- AlicenseNot gradedqualityAmaintenanceConnects 'yt-dlp' with LLMs via the Model Context Protocol, allowing users to download YouTube content and integrate it with Dive and other MCP-compatible LLMs.222 npm278MIT
- FlicenseAqualityDmaintenanceA Model Context Protocol server that enables Claude to interact with YouTube data and functionality through the Claude Desktop application.111-
- 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
- AlicenseNot gradedqualityCmaintenanceEnables Claude AI to extract transcripts from YouTube videos with zero local setup, supporting multi-language and all URL formats.MIT
- FlicenseAqualityDmaintenanceEnables fetching YouTube video transcripts in various formats via the Model Context Protocol, allowing LLMs to access and process YouTube video transcripts securely.1-
- AlicenseNot gradedqualityDmaintenanceAutomatically extracts subtitles, captures screenshots at specified timestamps, and generates structured Obsidian markdown notes from YouTube videos using Claude AI.3MIT
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool has a clear, singular purpose focused on downloading YouTube subtitles from a URL.
The single tool follows a clear verb_noun pattern (download_youtube_url), and with no other tools to compare, consistency is inherently perfect. The naming is descriptive and straightforward.
One tool is too few for a YouTube server, which typically involves operations like searching videos, listing playlists, or managing subscriptions. The scope feels incomplete and limited to a single niche function.
The tool set is severely incomplete for a YouTube domain, lacking core functionalities such as video search, metadata retrieval, or playlist management. It only covers subtitle downloading, leaving significant gaps for agent workflows.