Vidu MCP Server
A server that enables generating videos from static images using Vidu's AI models, with features for image-to-video conversion, task monitoring, and image uploading.
el-el-san
README
Vidu MCP Server
A Model Context Protocol (MCP) server for interacting with the Vidu video generation API. This server provides tools for generating videos from images using Vidu's powerful AI models.
Features
- Image to Video Conversion: Generate videos from static images with customizable settings
- Check Generation Status: Monitor the progress of video generation tasks
- Image Upload: Easily upload images to be used with the Vidu API
Prerequisites
- Node.js (v14 or higher)
- A Vidu API key (available from Vidu website)
- TypeScript (for development)
Installation
- Clone this repository:
git clone https://github.com/el-el-san/vidu-mcp-server.git
cd vidu-mcp-server
- Install dependencies:
npm install
- Create a
.env
file based on the.env.template
and add your Vidu API key:
VIDU_API_KEY=your_api_key_here
Usage
- Build the TypeScript code:
npm run build
- Start the server:
npm start
The MCP server will start and be ready to accept connections from MCP clients.
Tools
1. Image to Video
Converts a static image to a video with customizable parameters.
Parameters:
image_url
(required): URL of the image to convert to videoprompt
(optional): Text prompt for video generation (max 1500 chars)duration
(optional): Duration of the output video in seconds (4 or 8, default 4)model
(optional): Model name for generation ("vidu1.0", "vidu1.5", "vidu2.0", default "vidu2.0")resolution
(optional): Resolution of the output video ("360p", "720p", "1080p", default "720p")movement_amplitude
(optional): Movement amplitude of objects in the frame ("auto", "small", "medium", "large", default "auto")seed
(optional): Random seed for reproducibility
Example request:
{
"image_url": "https://example.com/image.jpg",
"prompt": "A serene lake with mountains in the background",
"duration": 8,
"model": "vidu2.0",
"resolution": "720p",
"movement_amplitude": "medium",
"seed": 12345
}
2. Check Generation Status
Checks the status of a running video generation task.
Parameters:
task_id
(required): Task ID returned by the image-to-video tool
Example request:
{
"task_id": "12345abcde"
}
3. Upload Image
Uploads an image to use with the Vidu API.
Parameters:
image_path
(required): Local path to the image fileimage_type
(required): Image file type ("png", "webp", "jpeg", "jpg")
Example request:
{
"image_path": "/path/to/your/image.jpg",
"image_type": "jpg"
}
How It Works
The server uses the Model Context Protocol (MCP) to provide a standardized interface for AI tools. When you start the server, it listens for commands through standard input/output channels and responds with results in a structured format.
The server handles all the complexity of interacting with the Vidu API, including:
- Authentication with API keys
- File uploads and format validation
- Asynchronous task management and polling
- Error handling and reporting
Troubleshooting
- API Key Issues: Make sure your Vidu API key is correctly set in the
.env
file - File Upload Errors: Check that your image files are valid and under 10MB in size
- Connection Problems: Ensure you have internet access and can reach the Vidu API servers
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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