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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 .docx or .md

Related MCP server: MCP YouTube Intelligence

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+

  • FFmpegbrew install ffmpeg (macOS) or apt-get install ffmpeg (Linux)

  • ANTHROPIC_API_KEY — set as an environment variable

Stylistic Fingerprint Fields

  1. Rendering Class — Stylized 3D, Flat 2D, Minimalist Line Art, Textured 2D, Mixed Media, Photoreal

  2. World Type — Stylized Real-World, Abstract Concept Space, Data/Presentation Space, Fictional Metaphor Universe

  3. Character Strategy — None, Mascot-Led, Single Narrator, Single Protagonist Arc, Ensemble Cast

  4. Narrative Structure — Direct Explanation, Step-by-Step, Problem-Solution, Analogy, Myth-Busting, etc.

  5. Visual Abstraction Index — 1 (Photorealistic) to 5 (Maximum Abstraction)

  6. Visual Density — Minimal, Sparse, Moderate, High

  7. Camera/Editing Language — Cinematic, Social Vertical Punch, Presentation Deck, Static Slides, etc.

  8. Tonal Positioning — Institutional, Corporate Professional, Gen Z Social, Child-Friendly, Dark Editorial

License

MIT

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quality - not tested
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maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

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