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Analyze videos: extract frames, transcribe audio, generate storyboard breakdowns.
About
Analyze videos: extract frames, transcribe audio, generate storyboard breakdowns.
Security Report
Valid MCP server (1 strong, 1 medium validity signals). 6 known CVEs in dependencies (1 critical, 4 high severity) Package registry verified. Imported from the Official MCP Registry.
5 files analyzed · 7 issues found
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Unverified package source
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How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-brightwayai-video-analyzer": {
"args": [
"video-analyzer-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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
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