Enables coding agents to watch and analyze videos by extracting scene-aware frames, transcribing speech, and generating shot timelines, all constrained by a token budget to fit LLM context limits.
Enables AI agents to download, transcribe, and inspect video or audio URLs from YouTube, TikTok, X, and 1000+ other sites using server-side yt-dlp, residential proxies, and speech-to-text.
Enables agents to analyze long videos by downloading them, extracting transcripts and storyboards, and zooming into specific moments with high-resolution frames and OCR.
Extracts ffprobe metadata, subtitles, scenes, and timelines from video files without frame-by-frame LLM vision, providing evidence-first reading for AI agents.
Lets any LLM agent actually watch videos: a watch_video tool takes a URL or local file and returns scene-aware keyframes fused with a timestamped transcript, processed 100% locally with per-source caching.
Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.