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mcp-video-analyser

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  • License MIT

MCP server for video analysis using Google Gemini and Moonshot Kimi AI

Package Exports

  • mcp-video-analyser
  • mcp-video-analyser/dist/index.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (mcp-video-analyser) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

mcp-video-analyser

A stdio-based MCP (Model Context Protocol) server for video analysis using Google Gemini and Moonshot Kimi AI.

Features

  • Analyze video files with AI vision models
  • Support for multiple providers: Google Gemini and Moonshot Kimi
  • Interactive setup wizard for easy configuration
  • User-scope or project-scope configuration
  • Environment variable support with fallback defaults
  • Video file validation (format, size, magic bytes)
  • TypeScript with strict type checking

Installation

npm install -g mcp-video-analyser
# or
bun install -g mcp-video-analyser

Quick Start

1. Run Setup

mcp-video-analyser setup

This will guide you through configuring your providers and API keys.

2. Configure Your MCP Client

Add to your MCP client configuration (e.g., Claude Desktop):

{
  "mcpServers": {
    "mcp-video-analyser": {
      "command": "mcp-video-analyser",
      "env": {
        "GOOGLE_API_KEY": "your-google-api-key",
        "MOONSHOT_API_KEY": "your-moonshot-api-key"
      }
    }
  }
}

3. Use the Tools

The server provides these MCP tools:

  • analyze_video - Analyze a local video file with an AI prompt
  • list_providers - List available providers and their models
  • get_config - View current configuration (API keys masked)

Configuration

Config File Locations

Scope Path
User (default) ~/.config/mcp-video-analyser/config.jsonc
Project ./.config/mcp-video-analyser/config.jsonc

Config Schema

{
  // Default provider: google or kimi
  "defaultProvider": "google",
  
  // Default model when not specified
  "defaultModel": "gemini-2.5-flash",
  
  // Provider configurations
  "providers": {
    "google": {
      // Supports: plain text, $ENV_VAR, ${ENV_VAR}, ${ENV_VAR:fallback}
      "apiKey": "${GOOGLE_API_KEY}",
      "enabled": true
    },
    "kimi": {
      "apiKey": "${MOONSHOT_API_KEY}",
      "baseUrl": "https://api.moonshot.ai/v1",
      "enabled": false
    }
  },
  
  // Video validation settings
  "video": {
    "maxSizeMB": 100,
    "supportedFormats": ["mp4", "webm", "mov", "avi", "mkv"]
  },
  
  // Analysis defaults
  "analysis": {
    "temperature": 0.6,
    "maxTokens": 8192
  }
}

Environment Variable Syntax

API keys in config support these formats:

"sk-your-plain-api-key"        # Plain text
"$GOOGLE_API_KEY"              # Direct env reference
"${GOOGLE_API_KEY}"            # Curly brace syntax
"${GOOGLE_API_KEY:fallback}"   # With fallback default

CLI Commands

# Interactive setup wizard
mcp-video-analyser setup

# Setup with explicit scope
mcp-video-analyser setup --scope user
mcp-video-analyser setup --scope project

# Start MCP server (default command)
mcp-video-analyser
mcp-video-analyser serve

# Show version
mcp-video-analyser --version

# Show help
mcp-video-analyser --help

Supported Providers

Google Gemini

Model Description
gemini-2.5-flash Recommended - fast & capable
gemini-2.5-pro Most powerful
gemini-2.0-flash Previous generation
gemini-1.5-pro Up to 1hr video
gemini-1.5-flash Budget-friendly

Requirements:

  • Google AI API key from Google AI Studio
  • Videos are uploaded via Google's File API for processing

Moonshot Kimi

Model Description
kimi-k2.5 Latest - multimodal agent
kimi-k2 Previous generation

Requirements:

  • Moonshot API key from Moonshot AI
  • Videos are sent as base64-encoded data

Supported Video Formats

  • MP4 (.mp4)
  • WebM (.webm)
  • QuickTime (.mov)
  • AVI (.avi)
  • Matroska (.mkv)

Maximum file size: 100 MB (configurable)

Development

Prerequisites

  • Node.js >= 20.0.0
  • Bun (recommended) or npm

Setup

# Clone the repository
git clone https://github.com/your-repo/mcp-video-analyser.git
cd mcp-video-analyser

# Install dependencies
bun install

# Build
bun run build

# Run in development
bun run dev

Scripts

Script Description
bun run build Compile TypeScript
bun run dev Run server in development
bun run dev:cli Run CLI in development
bun run setup Run setup wizard
bun run lint Run linting
bun run format Format code
bun run check Run all checks

Project Structure

mcp-video-analyser/
├── src/
│   ├── cli/                 # CLI commands
│   │   ├── commands/        # Individual commands
│   │   ├── prompts.ts       # @clack/prompts helpers
│   │   └── index.ts         # CLI entry point
│   ├── config/              # Configuration system
│   │   ├── env.ts           # Environment variable resolver
│   │   ├── paths.ts         # Config path resolution
│   │   ├── schema.ts        # Valibot schema
│   │   └── index.ts         # Config manager
│   ├── providers/           # AI provider implementations
│   │   ├── google/          # Google Gemini
│   │   ├── kimi/            # Moonshot Kimi
│   │   ├── types.ts         # Provider interface
│   │   └── index.ts         # Provider registry
│   ├── tools/               # MCP tools
│   │   ├── handlers/        # Tool implementations
│   │   └── definitions.ts   # Tool definitions
│   ├── utils/               # Utilities
│   │   ├── video.ts         # Video validation
│   │   └── schemas.ts       # Valibot schemas
│   ├── types/               # TypeScript types
│   └── index.ts             # MCP server entry
├── package.json
├── tsconfig.json
├── biome.json
└── mcp.json                 # Example MCP client config

License

MIT