Open source CapCut API tool.

中文说明

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

• 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

• /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

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

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

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

Install the required dependency packages for the project:

pip install -r requirements.txt

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.

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())

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())

import requests

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

print(response.json())

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 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"
        }
    }
}

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

• 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