By jayzes
Convert video and audio files into Claude-friendly markdown with transcripts and keyframes

(Yes, I know this is technically a Maxell ad, not a Memorex one. But it's a better image.)
Is it live, or is it Memorex?
Give Claude perfect recall of any video. Memorex converts video and audio into structured markdown with transcripts and keyframes—so Claude can see what you saw and hear what you heard.
Claude can't watch videos. But it can read markdown and view images. Memorex bridges that gap:
$ memorex demo.mp4
memorex
Processing: demo.mp4
Duration: 2m 34s
✓ Extracted 154 frames
✓ Found 12 keyframes
✓ Keyframes saved
✓ Audio extracted
✓ Transcribed 47 segments
✓ Markdown generated
✓ Output: demo_memorex.md
Frames: demo_memorex_frames/
Estimated tokens: ~15,600
Prerequisites: FFmpeg and whisper.cpp
# macOS
brew install ffmpeg whisper-cpp
# Ubuntu/Debian
sudo apt install ffmpeg
make install-whisper # builds whisper.cpp from source
Install memorex:
go install github.com/jayzes/memorex/cmd/memorex@latest
The Whisper model (~148MB) downloads automatically on first run.
memorex video.mp4 # Basic usage
memorex -t 0.9 presentation.mov # Fewer keyframes (fast-changing video)
memorex -t 0.7 interview.mp4 # More keyframes (static video)
memorex --no-frames podcast.mp3 # Audio only
memorex --no-transcript silent.mp4 # Video only
memorex -q 20 -s 0.3 huge.mp4 # Smaller output
Options:
| Flag | Default | Description |
|---|---|---|
-o, --output | <input>_memorex.md | Output path |
-t, --threshold | 0.85 | Frame similarity (lower = more keyframes) |
-q, --quality | 30 | JPEG quality (1-100) |
-s, --scale | 0.5 | Frame scale factor |
--no-transcript | Skip transcription | |
--no-frames | Skip frame extraction |
video_memorex.md
video_memorex_frames/
├── frame_0001.jpg
├── frame_0015.jpg
└── frame_0089.jpg
The markdown gives Claude everything it needs:
# Video Analysis: video.mp4
## Metadata
- Duration: 2m 34s
- Keyframes: 12
- Token estimate: ~15,600
## Transcript
[0:00] Welcome to this demonstration...
[0:15] As you can see on screen...
## Keyframes
### Frame 1 (0:00)

Let Claude handle everything automatically.
/plugin marketplace add jayzes/memorex
/plugin install memorex@jayzes-memorex
Then just ask Claude to analyze a video. It'll run memorex, read the output, and tell you what it sees.
make test # Run tests
make lint # Run linter
make fmt # Format code
| Problem | Solution |
|---|---|
| FFmpeg not found | brew install ffmpeg or apt install ffmpeg |
| whisper-cli not found | brew install whisper-cpp or make install-whisper |
| Out of memory | Use -s 0.25 -t 0.95 for large videos |
Fork, branch, code, test, PR. The usual.
MIT
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npx claudepluginhub jayzes/memorex --plugin memorexTurn videos into a sequence of relevant still frames + transcript + a self-contained HTML report so Claude can view them as images, hear the audio, and write its analysis back into the report. Pass a local path, an http(s) URL, or pipe video bytes on stdin.
Give Claude the ability to watch and understand videos — extracts frames and audio for full video perception
Turn any video into a section-by-section study-notes markdown file with embedded screenshots and a timestamped transcript.
Let Claude watch a video. Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls captions or falls back to Whisper, and hands frames + transcript to Claude so it can answer questions about the video.
Compose yt-dlp + ffmpeg + Whisper into a single command that hands an AI agent the raw materials to watch any social video — VIDEO + FRAMES + TRANSCRIPT, ready for an LLM to read frames as images and transcript as text.
Summarize videos, audio, and podcasts via BibiGPT CLI directly in the terminal