video-analyzer
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@video-analyzerAnalyze this YouTube video and provide a full storyboard breakdown"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: videoscan-mcp
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-mcpInstall 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 |
| Full pipeline: download, extract frames, transcribe, analyze, fingerprint, storyboard |
| Extract representative frames using scene detection or fixed intervals |
| Transcribe audio with OpenAI Whisper |
| Generate 8-field Stylistic Fingerprint v3 classification |
| Verify all required dependencies are installed |
Standalone Usage
pip install -r requirements.txt
python3 analyze_video.py "https://youtube.com/watch?v=..." --output-dir ./outputPrerequisites
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
This server cannot be deployed
Maintenance
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