Claude Code Video Vision
Give Claude the ability to watch and understand videos.
A Claude Code plugin that extracts frames via ffmpeg and processes audio via multiple backends (Gemini API, local Whisper, or OpenAI API). Claude receives frames as images and audio transcription with timestamps — the plugin is a perception layer, not an interpretation layer.
Features
- Multimodal perception — Claude sees video frames directly and reads audio transcriptions with timestamps
- YouTube URL support — Pass a YouTube URL directly; the MCP server downloads it with
yt-dlp, preserving source metadata and captions for context
- Flexible backends — Choose between cloud APIs or fully local processing
- Adaptive extraction — Claude adjusts fps, time range, and resolution based on your question
- Auto-installation — Whisper models download automatically on first use
- Interactive setup wizard —
/setup-video-vision walks you through configuration
Quick Start
1. Install the plugin
Inside Claude Code, run these commands one at a time:
/plugin marketplace add https://github.com/jordanrendric/claude-video-vision
Then:
/plugin install claude-video-vision
The MCP server will auto-install via npx from npm on first use — no build step required.
Alternative: local development
git clone https://github.com/jordanrendric/claude-video-vision.git
claude --plugin-dir /path/to/claude-video-vision
2. Configure
Inside Claude Code, run the interactive wizard:
/setup-video-vision
It will walk you through backend selection, whisper configuration (if local), frame options, and dependency verification.
Usage
Slash command
/watch-video path/to/video.mp4
/watch-video tutorial.mp4 "what language is used in this tutorial?"
/watch-video https://www.youtube.com/watch?v=... "summarize this video"
Conversational
Just mention a video file or YouTube URL — Claude will detect it:
"analyze this video for me: ~/Downloads/demo.mp4"
"take a look at the first second of ~/videos/bug-report.mov"
"summarize this YouTube Short: https://www.youtube.com/shorts/..."
Claude adapts parameters automatically:
- "the first second" → extracts at original fps from
00:00:00 to 00:00:01
- "summarize this 1h lecture" → low fps, full duration
- "what text is on screen at 1:30?" → high resolution, narrow time window
Backends
| Backend | Audio processing | Cost | Setup |
|---|
| Gemini API | Native (speech + non-speech events) | Free tier: 1500 req/day | GEMINI_API_KEY env var |
| Local (Whisper) | whisper.cpp or Python openai-whisper | Free, fully offline | brew install whisper-cpp + auto model download |
| OpenAI API | OpenAI Whisper API | Paid per usage | OPENAI_API_KEY env var |
All backends extract video frames via ffmpeg — Claude always has direct visual access.
Architecture
┌───────────────────────────────────────────────────────┐
│ Claude Code (your session) │
│ │
│ /watch-video ──→ Skill: video-perception │
│ │ │
│ ▼ │
│ MCP tool: video_watch │
│ │ │
└────────────────────────┼──────────────────────────────┘
│
▼
┌────────────────────────────────────┐
│ MCP Server (Node.js) │
│ │
│ ┌──────────┐ ┌──────────────┐ │
│ │ ffmpeg │ │ Audio backend│ │
│ │ frames │ ║ │ (parallel) │ │
│ └──────────┘ └──────────────┘ │
│ │ │ │
└───────┼─────────────────┼──────────┘
▼ ▼
base64 images transcription
+ timestamps + audio events
│ │
└────────┬────────┘
▼
Claude receives both
Requirements
- Node.js 20+ (for the MCP server)
- ffmpeg (auto-detected, install instructions provided by setup wizard)
- yt-dlp (optional, required only for YouTube URLs;
brew install yt-dlp on macOS)
- Backend-specific:
- Gemini API: free API key from ai.google.dev
- Local:
brew install whisper-cpp (macOS) or equivalent
- OpenAI: API key from OpenAI
MCP Tools
The plugin exposes 6 MCP tools:
