MCP

claude-video-vision

Give Claude the ability to watch and understand videos — Claude Code plugin with frame extraction and multimodal audio analysis

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claude-video-vision

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
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?"

Conversational

Just mention a video file — Claude will detect it:

"analyze this video for me: ~/Downloads/demo.mp4"

"take a look at the first second of ~/videos/bug-report.mov"

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)
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 4 MCP tools:

video_watch — Extract frames + process audio (main tool)
video_info — Get video metadata without processing
video_configure — Change settings
video_setup — Check and guide dependency installation

Slash Commands

/watch-video <path> [question] — Analyze a video
/setup-video-vision — Interactive configuration wizard

Configuration

Settings are stored in ~/.claude-video-vision/config.json:

{
  "backend": "local",
  "whisper_engine": "cpp",
  "whisper_model": "auto",
  "whisper_at": false,
  "frame_mode": "images",
  "frame_resolution": 512,
  "default_fps": "auto",
  "max_frames": 100,
  "frame_describer_model": "sonnet"
}

Whisper models auto-download to ~/.claude-video-vision/models/ on first use. Available: tiny, base, small, medium, large-v3-turbo, large-v3, auto (picks best for your RAM).