yt-mcp
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- FlicenseAqualityCmaintenanceEnables analysis of YouTube videos using the Gemini API to generate summaries and answer specific questions via direct URLs. It supports standard videos and shorts, allowing users to interact with video content without requiring manual downloads.510-
- AlicenseNot gradedqualityDmaintenanceAnalyzes public YouTube videos with Google Gemini, enabling summarization, timestamped insights, metadata extraction, audio analysis, and long-video sessions with follow-up questions.30 npm4MIT
- AlicenseBqualityDmaintenanceEnables conversational analysis of YouTube videos using Gemini 2.5 Pro, supporting multi-turn sessions, direct URL processing, and local video uploads.101MIT
- FlicenseBqualityDmaintenanceEnables AI-powered YouTube video analysis including transcript management, video summaries, chapter generation, keyword extraction, and playback control. Supports searching videos, retrieving channel/playlist information, and translating transcripts using Google Gemini AI.14-
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to analyze YouTube videos by extracting summaries, timestamped outlines, diagrams with Mermaid code, and targeted insights about specific moments using Gemini's native video understanding.MIT
- AlicenseAqualityBmaintenanceEnables MCP clients like Claude to analyze public YouTube videos by asking questions grounded in both audio and visuals through the Google Gemini API.11MIT
TDQS
Scored across 5 tools
Tools are mostly distinct: ask_about_video and summarize_video both deal with content analysis but differ in question vs. summary. extract_frames and extract_screenshots have clear differences (given timestamps vs. AI-chosen moments). get_video_timestamps is a preview for extraction, reducing overlap. Minor confusion possible between ask_about_video and summarize_video.
All tool names use verb_* pattern with snake_case (ask_about_video, extract_frames, etc.), which is consistent. Some verbs are compound (ask_about), but the pattern is predictable and clear.
5 tools is appropriate for a YouTube MCP: they cover core operations (summarize, Q&A, frame extraction, screenshot extraction, timestamp preview). Not too few or too many.
The tool set covers main user needs: summarization, Q&A, and visual extraction with a preview step. Missing operations like searching videos or managing playlists, but those may be out of scope. The workflow from preview to extraction is well-supported.