-
securityA
license-
qualityA server that provides AI-powered image generation, modification, and processing capabilities through the Model Context Protocol, leveraging Google Gemini models and other image services.
Last updated -
15
MIT License
The Vidu MCP Server is a tool for interacting with the Vidu API that enables:
Generate Videos from Images: Create videos from static images with customizable settings including duration, resolution, prompt, model, movement amplitude, and seed.
Monitor Task Progress: Check the status of ongoing video generation tasks using a task ID.
Upload Images: Upload local images (PNG, WebP, JPEG) to use in the video generation process.
Uses environment variables for configuration, particularly for storing and accessing the Vidu API key securely.
Hosted on GitHub, allowing users to clone the repository for installation and potentially contribute to the project.
Runs on Node.js platform (v14 or higher), leveraging its JavaScript runtime for the server implementation.
Uses npm for package management and running scripts (build, start) for the server.
Built with TypeScript for type-safe development, requiring compilation before running the server.
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
Installing via Smithery
To install Vidu Video Generation Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @el-el-san/vidu-mcp-server --client claude
Manual 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
.envfile based on the.env.templateand 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
.envfileFile 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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