MCP Video Generation with Veo2
MCP server that exposes Google's Veo2 video generation capabilities, allowing clients to generate videos from text prompts or images.
README
MCP Video Generation with Veo2
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.
Features
- 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
Example Images
Example Image to Video
Image to Video - from Grok generated puppy
Image to Video - from real cat
Prerequisites
- 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 )
Installation
Installing in FLUJO
- Click Add Server
- Copy & Paste Github URL into FLUJO
- Click Parse, Clone, Install, Build and Save.
Installing via Smithery
To install mcp-video-generation-veo2 for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @mario-andreschak/mcp-veo2 --client claude
Manual Installation
-
Clone the repository:
git clone https://github.com/yourusername/mcp-video-generation-veo2.git cd mcp-video-generation-veo2 -
Install dependencies:
npm install -
Create a
.envfile with your Google API key:cp .env.example .env # Edit .env and add your Google API keyThe
.envfile 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
debugorinfofor more detailed logs - For production, keep as
fatalto minimize console output
-
Build the project:
npm run build
Usage
Starting the Server
You can start the server with either stdio or SSE transport:
stdio Transport (Default)
npm start
# or
npm start stdio
SSE Transport
npm start sse
This will start the server on port 3000 (or the port specified in your .env file).
MCP Tools
The server exposes the following MCP tools:
generateVideoFromText
Generates a video from a text prompt.
Parameters:
prompt(string): The text prompt for video generationconfig(object, optional): Configuration optionsaspectRatio(string, optional): "16:9" or "9:16"personGeneration(string, optional): "dont_allow" or "allow_adult"numberOfVideos(number, optional): 1 or 2durationSeconds(number, optional): Between 5 and 8enhancePrompt(boolean, optional): Whether to enhance the promptnegativePrompt(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
}
}
generateVideoFromImage
Generates a video from an image.
Parameters:
image(string): Base64-encoded image dataprompt(string, optional): Text prompt to guide the video generationconfig(object, optional): Configuration options (same as above, but personGeneration only supports "dont_allow")
listGeneratedVideos
Lists all generated videos.
MCP Resources
The server exposes the following MCP resources:
videos://{id}
Access a generated video by its ID.
videos://templates
Access example video generation templates.
Development
Project Structure
src/: Source codeindex.ts: Main entry pointserver.ts: MCP server configurationconfig.ts: Configuration handlingtools/: MCP tool implementationsresources/: MCP resource implementationsservices/: External service integrationsutils/: Utility functions
Building
npm run build
Development Mode
npm run dev
License
MIT
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