Enables MCP clients to transcribe audio/video files locally, generate SRT subtitles, and burn captions into videos via tool calls, without a cloud API.
Enables AI clients to watch local video files or YouTube/Bilibili and other supported URLs, receiving timestamped transcripts, subtitles, searchable text and keyframe contact sheets. Runs fully offline with local speech recognition and bundled ffmpeg, so no API key or cloud upload is needed.
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.
Enables an agent to process local video files and then read, search and inspect the results: timestamped transcripts, on-screen text and key frames as images. Everything runs locally, so an agent can answer questions like how to perform a task shown in a screencast or meeting recording.
Enables downloading videos from platforms like YouTube and converting them to text using OpenAI Whisper and ffmpeg. It supports multiple output formats including TXT, JSON, SRT, and VTT for transcriptions.