Builds a searchable knowledge base from YouTube video transcripts with hybrid semantic and keyword search. Allows LLM assistants to search, organize, and retrieve timestamped information from videos you've watched.
Transforms YouTube into a queryable knowledge source with search, video details, transcript analysis, and AI-powered tools for summaries, learning paths, and knowledge graphs. Features quota-aware API access with caching and optional OpenAI/Anthropic integration for advanced content analysis.
Transforms YouTube videos into LLM-ready knowledge bases through transcription, semantic chunking, and vector embedding services. It provides 12 specialized MCP tools for video processing, semantic search, and SEO intelligence analysis.
Enables extraction of transcripts, keyword-based video search with metadata retrieval, and channel information discovery from YouTube videos through natural language interaction.
Enables AI assistants to watch YouTube videos by extracting frames at scene changes and visual references, pairing each frame with the exact words spoken at that timestamp. Provides dense frame-transcript interleaving for any model.
