youtube-research-mcp
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- AlicenseCqualityBmaintenanceEnables AI agents to search, analyze, and extract insights from YouTube videos including transcripts, visual frames, and benchmarks without requiring API keys. Supports semantic search across playlists, sentiment analysis, and visual content indexing with automatic fallback chains for reliable access.41162 npm35MIT
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- AlicenseAqualityBmaintenanceEnables read-only research on YouTube by exposing video metadata, transcripts, comments, search, channels, playlists, and trending data through four task-oriented tools.4MIT
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TDQS
Scored across 4 tools
Each tool addresses a distinct stage of a clear research workflow: finding videos (search_youtube), surveying a channel (list_channel_videos), extracting text (get_video_transcript), and capturing visual evidence (get_video_frames). There is no functional overlap; even list_channel_videos and search_youtube produce different result sets with different intents.
All tool names follow the consistent verb_noun pattern: list_channel_videos, get_video_transcript, search_youtube, get_video_frames. Verbs are specific to the action, and objects clearly indicate the resource, making the set predictable and easy to navigate.
Four tools is an ideal size for a focused research MCP. Each tool is essential to the workflow and there are no redundant or filler tools, making the set feel tight and purposeful.
The tool surface covers the complete research lifecycle from topic-based search to channel exploration to transcript and frame extraction. All returned data includes video metadata, and the workflow is explicitly documented within the descriptions, leaving no obvious dead ends for a research agent.