MCP server for video analysis — extracts transcripts, key frames with OCR, and annotated timelines from video URLs. Supports Loom and direct video files (.mp4, .webm). Zero auth required.
An MCP server for image and video processing that allows AI assistants to resize, convert, compress, and analyze media files locally without API keys. It supports a wide range of formats and provides tools for tasks such as metadata removal, frame extraction, and video conversion.
Gives AI agents video perception by turning screen recordings, films and URLs into timestamped structured evidence: ordered UI states and transitions, per-screen OCR, shots, camera motion, palettes, on-screen text and speech, all cached locally with no API keys. Includes drill-down tools to zoom into intervals, crop full-resolution frames, diff two moments, and search on-screen text and speech across everything watched.
Converts screen-recorded walkthrough videos into timestamped transcripts, extracted frames, scene-change anchors, and interleaved slices that pair each frame with the speech following it, so a coding assistant can read video feedback. All processing runs locally via ffmpeg and Whisper, with results cached to disk and exportable as transcript, frame images, and a README skeleton.
Provides image and video analysis capabilities for LLMs, with local preprocessing (ffmpeg/OpenCV) and any OpenAI-compatible vision model for understanding and Q&A.
Enables local video understanding by generating numbered storyboard sheets with timecoded transcripts, zooming into selected segments, locating spoken phrases, probing media metadata, and tracking playback progress. It uses local ffmpeg and optional offline speech recognition.
Enables AI agents to analyze videos by producing timestamped transcripts, keyframe contact sheets, and metadata reports from local files or online URLs, fully offline and without API keys.
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.