video-brief-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables 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.MIT

9xvisionofficial
AlicenseBqualityBmaintenanceGives 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.153MIT- AlicenseAqualityBmaintenanceEnables Claude Code, Codex, Claude Desktop and Cursor to see and hear MP4/MOV/MKV/WebM videos and screen recordings through timestamped keyframe storyboards, zoom and full-resolution frame drill-down, and a locally generated Whisper transcript. It also works with recording bundles that capture clicks and typed context, and runs entirely on the user's machine with no uploads or API keys.5MIT
- AlicenseNot gradedqualityDmaintenancevidlizer pulls frames out of any video, image, or PDF using ffmpeg, sends them to a vision LLM, and returns a flow array — one entry per scene. Each entry tells you what happened, who was on screen, what text was visible, and what changed. If the video has audio, it transcribes it with Apple MLX Whisper and merges the speech into each step.25 PyPI4MIT
- FlicenseAqualityDmaintenanceExtracts timestamped screenshots from local videos, enabling Claude to produce visual walkthroughs without audio analysis or cloud processing.4-
- FlicenseNot gradedqualityDmaintenanceGenerates narrated video walkthroughs of git commits, staged/unstaged changes, or entire codebases with AI-powered analysis, syntax-highlighted code visualization, and text-to-speech narration.-
TDQS
Scored across 7 tools
Each tool has a distinct role, but frames can be produced three ways (brief_frames, brief_scenes with withFrames, brief_slice), and brief_transcribe vs brief_transcript could initially be confused (start/monitor vs read cached). The descriptions do a good job of delineating these, noting defaults, caps, and when to use which.
All tools share a consistent brief_ prefix in snake_case, so the set reads as a coherent family. The suffix style is mixed (verbs like probe/transcribe/slice/export vs nouns like transcript/frames/scenes), which is a minor deviation but still predictable.
Seven tools is well within a comfortable range, and each covers a discrete step of the video-briefing workflow (inspect, transcribe, read, sample, detect, interleave, export). No tool looks redundant or tacked on.
The surface covers the full lifecycle from probing a file through transcription, evidence gathering, and exporting artifacts to a folder. Minor gaps remain: no cache cleanup/management, no options for transcription model or language, and no explicit error/recovery path for corrupt files.