Videocutter
V

Videocutter

VideoCutter is a professional multimedia tool that integrates video, audio, and image processing. It supports AI - intelligent editing and the MCP protocol, providing a one - stop intelligent creation solution.
2 points
5.4K

What is the VideoCutter MCP server?

The VideoCutter MCP server is a professional media processing service based on the Model Context Protocol. It enables AI agents to call 67 professional tools such as video editing, audio processing, and image editing through natural language. It supports two transmission modes, SSE and HTTP Streamable, providing powerful multimedia processing capabilities for AI applications.

How to use the VideoCutter MCP server?

You can use an AI agent to describe your media processing requirements in natural language, for example, 'Help me crop this video to 1 minute in length and add subtitles'. The server supports two connection methods: the SSE mode for real-time progress monitoring and the HTTP Streamable mode for complex interaction scenarios.

Applicable scenarios

It is suitable for scenarios that require media processing, such as content creation, short - video production, podcast editing, education and training, and corporate promotion. Both individual creators and professional teams can quickly complete complex media processing tasks through AI agents.

Main Features

Video Processing
Supports complete video editing functions such as video splitting, merging, speed change, rotation, cropping, filters, color adjustment, overlay synthesis, etc.
Audio Processing
Provides professional audio processing tools such as audio splitting, merging, speed change, volume adjustment, fade - in and fade - out, reverb effects, and vocal enhancement.
Image Processing
Includes comprehensive image editing functions such as image cropping, rotation, scaling, filters, special effects, overlay synthesis, and format conversion.
AI Generation Function
Integrates AI models for text generation, image generation, and video generation, supporting creation functions such as text - to - image, text - to - video, and image - to - video conversion.
Batch Processing
Supports batch overlay of images and text through command files, greatly improving processing efficiency. It supports an 81 - grid precise positioning system.
MCP Agent Integration
Deeply supports AI agents to call 67 professional tools through natural language, supporting both SSE and HTTP Streamable transmission modes.
Advantages
One - stop media processing: Integrates three major processing modules for video, audio, and images to meet all editing needs.
AI intelligent optimization: Built - in multiple AI models provide intelligent text, image, and video generation capabilities.
Natural language interaction: Supports AI agents to call complex functions in natural language through the MCP protocol.
Dual transmission modes: Supports both SSE real - time monitoring and HTTP Streamable two - way interaction modes.
Precise positioning system: A unique 81 - grid positioning system provides pixel - level precise control.
Batch processing efficiency: Supports batch operations, greatly improving processing efficiency.
Limitations
Requires certain hardware resources: AI models and video processing require good CPU and GPU performance.
Learning curve: Although natural language is supported, complex functions still require an understanding of basic concepts.
Network dependency: Cloud - based AI services require a stable network connection.
File size limitation: Processing extremely large files may be limited by memory.

How to Use

Start the MCP Server
Ensure that the VideoCutter service is running normally. The MCP server will automatically start on ports 8000 (SSE) and 8001 (HTTP Streamable).
Connect the AI Agent
Configure your AI application or agent to connect to the MCP server, using the corresponding server address and transmission mode.
Use Natural Language to Call Functions
Use an AI agent to describe your needs in natural language, such as video editing, audio processing, and image editing tasks.
Monitor the Processing Progress
Monitor the progress of long - running processing tasks in real - time through the SSE mode, or conduct real - time interaction through the HTTP Streamable mode.

Usage Examples

Short - Video Editing and Production
A user wants to create a 15 - second short video for social media sharing, which requires cropping the video, adding filters, inserting text, and background music.
Podcast Audio Processing
A user has recorded a podcast audio and needs to remove noise, standardize the volume, add fade - in and fade - out effects, and extract the subtitle text of the key content.
Product Promotion Image Creation
A user needs to create a promotional image for a new product, including product image modification, text addition, and multi - image synthesis.

Frequently Asked Questions

What is the MCP server? How is it different from a regular API?
What is the difference between the SSE mode and the HTTP Streamable mode? Which one should I choose?
Do I need programming knowledge to use the MCP server?
What file formats are supported? Are there any size limitations?
What should I do if an error occurs during the processing?

Related Resources

VideoCutter GitHub Repository
The project's source code and latest updates
VideoCutter Gitee Repository
A domestic mirror repository with faster access speed
API Usage Documentation
Detailed REST API interface description and usage guide
MCP Tool Documentation
Complete list of MCP tools and usage methods
AI Model Usage Instructions
AI function configuration and model usage guide
Detailed Explanation of Position Parameters
Detailed description and examples of the 81 - grid positioning system

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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