This project implements a Model Context Protocol (MCP) server that exposes Google's Veo2 video generation capabilities. It allows clients to generate videos from text prompts or images, and access the generated videos through MCP resources.

• Generate videos from text prompts
• Generate videos from images
• Access generated videos through MCP resources
• Example video generation templates
• Support for both stdio and SSE transports

Image to Video - from Grok generated puppy

Image to Video - from real cat

• Node.js 18 or higher
• Google API key with access to Gemini API and Veo2 model (= You need to set up a credit card with your API key! -> Go to aistudio.google.com )

1. Click Add Server
2. Copy & Paste Github URL into FLUJO
3. Click Parse, Clone, Install, Build and Save.

To install mcp-video-generation-veo2 for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @mario-andreschak/mcp-veo2 --client claude

1. Clone the repository:

   git clone https://github.com/yourusername/mcp-video-generation-veo2.git
   cd mcp-video-generation-veo2

2. Install dependencies:

   npm install

3. Create a .env file with your Google API key:

   cp .env.example .env
   # Edit .env and add your Google API key

   The .env file supports the following variables:

   • GOOGLE_API_KEY: Your Google API key (required)
   • PORT: Server port (default: 3000)
   • STORAGE_DIR: Directory for storing generated videos (default: ./generated-videos)
   • LOG_LEVEL: Logging level (default: fatal)
     • Available levels: verbose, debug, info, warn, error, fatal, none
     • For development, set to debug or info for more detailed logs
     • For production, keep as fatal to minimize console output

4. Build the project:

   npm run build

You can start the server with either stdio or SSE transport:

npm start
# or
npm start stdio

npm start sse

This will start the server on port 3000 (or the port specified in your .env file).

The server exposes the following MCP tools:

Generates a video from a text prompt.

Parameters:

• prompt (string): The text prompt for video generation
• config (object, optional): Configuration options
  • aspectRatio (string, optional): "16:9" or "9:16"
  • personGeneration (string, optional): "dont_allow" or "allow_adult"
  • numberOfVideos (number, optional): 1 or 2
  • durationSeconds (number, optional): Between 5 and 8
  • enhancePrompt (boolean, optional): Whether to enhance the prompt
  • negativePrompt (string, optional): Text describing what not to generate

Example:

{
  "prompt": "Panning wide shot of a serene forest with sunlight filtering through the trees, cinematic quality",
  "config": {
    "aspectRatio": "16:9",
    "personGeneration": "dont_allow",
    "durationSeconds": 8
  }
}

Generates a video from an image.

Parameters:

• image (string): Base64-encoded image data
• prompt (string, optional): Text prompt to guide the video generation
• config (object, optional): Configuration options (same as above, but personGeneration only supports "dont_allow")

Lists all generated videos.

The server exposes the following MCP resources:

Access a generated video by its ID.

Access example video generation templates.

• src/: Source code
  • index.ts: Main entry point
  • server.ts: MCP server configuration
  • config.ts: Configuration handling
  • tools/: MCP tool implementations
  • resources/: MCP resource implementations
  • services/: External service integrations
  • utils/: Utility functions

npm run build

npm run dev

MIT