What can you do with this server?

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.

Which integrations are available for this server?

Uses environment variables for configuration, particularly for storing and accessing the Vidu API key securely. Hosted on [GitHub](/mcp/servers/integrations/github), allowing users to clone the repository for installation and potentially contribute to the project. Runs on [Node.js](/mcp/servers/integrations/node-dot-js) platform (v14 or higher), leveraging its JavaScript runtime for the server implementation. Uses [npm](/mcp/servers/integrations/npm) for package management and running scripts (build, start) for the server. Built with [TypeScript](/mcp/servers/integrations/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

Related MCP server: Ghibli Video MCP Server

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 .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 video
prompt (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 file
image_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