Summary
Gives Claude five tools to break down video content without leaving the chat. Point it at a YouTube URL or local file and video_analyze runs the full pipeline: scene detection pulls keyframes, Whisper transcribes the audio with timestamps, Claude Vision describes each frame, and you get back an eight-field stylistic fingerprint classifying everything from rendering style to tonal positioning. You can also call the steps individually if you just need transcription or frame extraction. Requires FFmpeg locally and an Anthropic API key in the environment. Outputs storyboards as Markdown or DOCX, useful when you're analyzing reference videos, auditing content at scale, or feeding visual context into longer creative briefs.
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Video Analyzer
Analyze videos and generate storyboard breakdowns. Extracts frames via scene detection, transcribes audio with Whisper, analyzes visuals with Claude Vision, and computes 8-field stylistic fingerprints.
Features
- Frame Extraction — Scene-detection-based keyframe selection (or fixed intervals)
- Audio Transcription — Timestamped transcription via OpenAI Whisper
- Visual Analysis — Per-frame descriptions using Claude Vision
- Stylistic Fingerprint v3 — 8-field deterministic classification (rendering class, world type, character strategy, narrative structure, visual abstraction, visual density, camera language, tonal positioning)
- Storyboard Output — Combined shot-by-shot breakdown as
.docxor.md
MCP Server
This project includes an MCP (Model Context Protocol) server so you can use video analysis directly from Claude Desktop or Claude Code.
Install via Claude Code
claude mcp add video-analyzer -s user -- uvx video-analyzer-mcp
Install via Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"video-analyzer": {
"command": "uvx",
"args": ["video-analyzer-mcp"],
"env": {
"ANTHROPIC_API_KEY": "your-key-here"
}
}
}
}
MCP Tools
| Tool | Description |
|---|---|
video_analyze | Full pipeline: download, extract frames, transcribe, analyze, fingerprint, storyboard |
video_extract_frames | Extract representative frames using scene detection or fixed intervals |
video_transcribe | Transcribe audio with OpenAI Whisper |
video_fingerprint | Generate 8-field Stylistic Fingerprint v3 classification |
video_check_deps | Verify all required dependencies are installed |
Standalone Usage
pip install -r requirements.txt
python3 analyze_video.py "https://youtube.com/watch?v=..." --output-dir ./output
Prerequisites
- Python 3.10+
- FFmpeg —
brew install ffmpeg(macOS) orapt-get install ffmpeg(Linux) - ANTHROPIC_API_KEY — set as an environment variable
Stylistic Fingerprint Fields
- Rendering Class — Stylized 3D, Flat 2D, Minimalist Line Art, Textured 2D, Mixed Media, Photoreal
- World Type — Stylized Real-World, Abstract Concept Space, Data/Presentation Space, Fictional Metaphor Universe
- Character Strategy — None, Mascot-Led, Single Narrator, Single Protagonist Arc, Ensemble Cast
- Narrative Structure — Direct Explanation, Step-by-Step, Problem-Solution, Analogy, Myth-Busting, etc.
- Visual Abstraction Index — 1 (Photorealistic) to 5 (Maximum Abstraction)
- Visual Density — Minimal, Sparse, Moderate, High
- Camera/Editing Language — Cinematic, Social Vertical Punch, Presentation Deck, Static Slides, etc.
- Tonal Positioning — Institutional, Corporate Professional, Gen Z Social, Child-Friendly, Dark Editorial
License
MIT
Featured
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →Registryactive
Packagevideo-analyzer-mcp
TransportSTDIO
UpdatedMar 10, 2026
