video-mcp
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AlicenseNot gradedqualityCmaintenanceSelf-hosted video intelligence pipeline that turns video into structured, citable, queryable JSON scene graphs, enabling AI assistants to analyze and search across video libraries without re-processing.5 npm1MIT- AlicenseAqualityBmaintenanceEnables 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.6MIT
- AlicenseNot gradedqualityAmaintenanceProvides local, offline transcription, keyframe extraction, OCR, and pre-publish review of audio, video, and image files, enabling AI agents to see and hear media without cloud or API keys.90 npmApache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables 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.MIT
- -licenseBqualityNot gradedmaintenanceEnables comprehensive video file metadata management including reading, editing, and batch processing of video properties like title, description, tags, and technical specifications. Supports multiple video formats with intelligent caching and search capabilities.89 npm1-
- AlicenseBqualityCmaintenanceEnables AI agents to edit videos locally by inspecting media, applying templates, cutting clips, and delivering finished files, with memory of human preferences.183Apache 2.0
TDQS
Scored across 9 tools
Each tool has a clear primary role: analyze for full pipeline, transcribe for speech, ocr for text, frames for visuals, info for metadata, search for locating moments, and deps for setup. The only overlap is video_analyze, which combines several primitives, but its description explicitly directs when to use it, so agents should not be misled.
All tools share the video_ prefix and use lowercase, underscore-separated action-oriented names such as video_extract_frames and video_get_frame_burst. The main deviation is video_info, which uses a noun rather than a verb, but the pattern is otherwise consistent.
Nine tools is well-scoped for a video-processing MCP server. Each tool covers a distinct part of the video-understanding workflow, from dependency checking and metadata probing to transcription, OCR, frame extraction, and combined analysis, without unnecessary bloat.
The surface covers all major video analysis needs: metadata, transcripts, searching, frame extraction, OCR, and a one-shot summary. There are no obvious dead ends—dependencies are checked, and tools are designed to feed into each other (e.g., transcript timestamps to video_get_frame).