Fetches YouTube transcripts and enables semantic search within them using local embeddings, allowing an LLM to retrieve relevant passages with timestamps.
Enables AI agents to search videos, retrieve metadata and transcripts, pinpoint exact moments via hybrid semantic search, and conduct multi-video research with timestamp deep links—all without YouTube API keys.
Transforms YouTube videos into a persistent, structured knowledge base using transcripts and visual frame analysis, enabling knowledge compounding and natural language querying.
Enables search across videos you've watched via transcripts, on-screen text, and frames, citing exact timestamps. Point it at videos, channels, or playlists; it indexes everything locally and answers queries with deep links to the exact second.
Enables users to turn YouTube videos into a compounding, searchable knowledge base by combining transcripts with vision analysis and agentic retrieval, while serving that capability to MCP clients like Claude and Copilot.