R

Runwayml + Luma AI

A multi - functional MCP server integrating RunwayML and Luma AI APIs, supporting video/image generation and processing tasks
2.5 points
24

What is the RunwayML + Luma AI MCP Server?

This is a server based on the MCP protocol, aiming to provide powerful video and image generation capabilities through the RunwayML and Luma AI APIs. Users can easily create high - quality visual content, such as text - to - video, image - to - video, and image generation.

How to use the RunwayML + Luma AI MCP Server?

With simple commands and configurations, you can quickly start the server and begin generating content. Just install the necessary dependencies and set up the API keys to start using it.

Applicable Scenarios

Suitable for creative workers, advertisers, and developers who need to quickly generate high - quality video and image content. Whether it's making short videos, animations, or product demonstrations, this server can meet your needs.

Main Features

Text - to - Video GenerationGenerate high - quality videos based on text prompts, supporting RunwayML and Luma AI models.
Image - to - Video GenerationConvert existing images into dynamic videos, supporting multiple animation effects.
Image GenerationGenerate high - resolution images based on text prompts, supporting multiple models of Luma AI.
Audio AdditionAdd background music or sound effects to the generated videos or images.
Image UpscalingUse Luma AI technology to perform high - quality upscaling on images.

Advantages and Limitations

Advantages
Supports multiple AI models, with powerful and diverse functions.
Easy to integrate into existing workflows.
Can quickly generate high - quality content without complex programming.
Supports real - time progress updates and result feedback.
Limitations
Requires a stable network connection to ensure a smooth generation process.
Some advanced functions may require additional computing resources.
API key management needs to be done carefully to avoid leakage of sensitive information.

How to Use

Install and Configure the Server
Clone the project code and install the dependencies, then create a.env file in the server directory to store the API keys.
Start the Server
Compile the TypeScript code and start the server to ensure it runs normally.
Configure the Client
Configure the server address and environment variables in the MCP client.

Usage Examples

Music Video ClipGenerate a 5 - second video of a future city夜景.
Product AdvertisementGenerate a video showing the floating effect of future wireless earbuds.

Frequently Asked Questions

What dependencies are required to run the server?
How to ensure the quality of the generated videos?
Does it support batch generation?

Related Resources

Official Documentation
RunwayML official documentation.
GitHub Code Repository
The open - source code repository of the project.
Tutorial Video
Quick - start tutorial.
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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