capcut-mcp

capcut-mcp

Automates CapCut video editing through an HTTP/MCP API, enabling draft creation, material addition (video, audio, text, images), effects, and AI-powered enhancements via natural language.

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README

CapCutAPI

Open source CapCut API tool.

中文说明

Project Features

This project is a Python-based CapCut processing tool that offers the following core functionalities:

Core Features

  • Draft File Management: Create, read, modify, and save CapCut draft files
  • Material Processing: Support adding and editing various materials such as videos, audios, images, texts, stickers, etc.
  • Effect Application: Support adding multiple effects like transitions, filters, masks, animations, etc.
  • API Service: Provide HTTP API interfaces to support remote calls and automated processing
  • AI Integration: Integrate multiple AI services to support intelligent generation of subtitles, texts, and images

Main API Interfaces

  • /create_draft: Create a draft
  • /add_video: Add video material to the draft
  • /add_audio: Add audio material to the draft
  • /add_image: Add image material to the draft
  • /add_text: Add text material to the draft
  • /add_subtitle: Add subtitles to the draft
  • /add_effect: Add effects to materials
  • /add_sticker: Add stickers to the draft
  • /save_draft: Save the draft file

Configuration Instructions

Configuration File

The project supports custom settings through a configuration file. To use the configuration file:

  1. Copy config.json.example to config.json
  2. Modify the configuration items as needed
cp config.json.example config.json

Environment Configuration

ffmpeg

This project depends on ffmpeg. You need to ensure that ffmpeg is installed on your system and added to the system's environment variables.

Python Environment

This project requires Python version 3.8.20. Please ensure that the correct version of Python is installed on your system.

Install Dependencies

Install the required dependency packages for the project:

pip install -r requirements.txt

Run the Server

After completing the configuration and environment setup, execute the following command to start the server:

python main.py

Once the server is started, you can access the related functions through the API interfaces.

Usage Examples

Adding a Video

import requests

response = requests.post("http://localhost:9000/add_video", json={
    "video_url": "http://example.com/video.mp4",
    "start": 0,
    "end": 10,
    "width": 1080,
    "height": 1920
})

print(response.json())

Adding Text

import requests

response = requests.post("http://localhost:9000/add_text", json={
    "text": "Hello, World!",
    "start": 0,
    "end": 3,
    "font": "Source Han Sans",
    "font_color": "#FF0000",
    "font_size": 30.0
})

print(response.json())

Saving a Draft

import requests

response = requests.post("http://localhost:9000/save_draft", json={
    "draft_id": "123456",
    "draft_folder": "your capcut draft folder"
})

print(response.json())

Copying the Draft to CapCut Draft Path

Calling save_draft will generate a folder starting with dfd_ in the current directory of the server. Copy this folder to the CapCut draft directory, and you will be able to see the generated draft.

Configure MCP

Configure MCP in Cursor. In the Cursor settings, add an MCP server with the address http://localhost:9000/mcp, and then you can use MCP in Cursor.

In the Claude configuration, add the following content:

{
    "mcpServers": {
        "capcut-mcp": {
            "type": "http",
            "url": "http://localhost:9000/mcp"
        }
    }
}

More Examples

Please refer to the example.py file in the project, which contains more usage examples such as adding audio and effects.

Project Features

  • Cross-platform Support: Supports both CapCut China version and CapCut International version
  • Automated Processing: Supports batch processing and automated workflows
  • Rich APIs: Provides comprehensive API interfaces for easy integration into other systems
  • Flexible Configuration: Achieve flexible function customization through configuration files
  • AI Enhancement: Integrate multiple AI services to improve video production efficiency

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