CapCutAPI is a powerful editing API that empowers you to take full control of your AI-generated assets, including images, audio, video, and text. It provides the precision needed to refine and customize raw AI output, such as adjusting video speed or mirroring an image. This capability effectively solves the lack of control often found in AI video generation, allowing you to easily transform your creative ideas into polished videos.

All these features are designed to mirror the functionalities of the CapCut software, ensuring a familiar and efficient editing experience in the cloud.

Enjoy It! 😀😀😀

中文说明

1. API-Powered Editing: Access all CapCut/Jianying editing features, including multi-track editing and keyframe animation, through a powerful API.

2. Real-Time Cloud Preview: Instantly preview your edits on a webpage without downloads, dramatically improving your workflow.

3. Flexible Local Editing: Export projects as drafts to import into CapCut or Jianying for further refinement.

4. Automated Cloud Generation: Use the API to render and generate final videos directly in the cloud.

• Python 3.10+
• Jianying or CapCut International version
• FFmpeg

# 1. Clone the project
git clone https://github.com/sun-guannan/CapCutAPI.git
cd CapCutAPI

# 2. Create a virtual environment (recommended)
python -m venv venv-capcut
source venv-capcut/bin/activate  # Linux/macOS
# or venv-capcut\Scripts\activate  # Windows

# 3. Install dependencies
pip install -r requirements.txt      # HTTP API basic dependencies
pip install -r requirements-mcp.txt  # MCP protocol support (optional)

# 4. Configuration file
cp config.json.example config.json
# Edit config.json as needed

python capcut_server.py # Start the HTTP API server, default port: 9001

python mcp_server.py # Start the MCP protocol service, supports stdio communication

MCP 中文文档 • MCP English Guide

Create or update the mcp_config.json configuration file:

{
  "mcpServers": {
    "capcut-api": {
      "command": "python3",
      "args": ["mcp_server.py"],
      "cwd": "/path/to/CapCutAPI",
      "env": {
        "PYTHONPATH": "/path/to/CapCutAPI",
        "DEBUG": "0"
      }
    }
  }
}

# Test MCP connection
python test_mcp_client.py

# Expected output
✅ MCP server started successfully
✅ Got 11 available tools
✅ Draft creation test passed

Add video material

import requests

# Add background video
response = requests.post("http://localhost:9001/add_video", json={
    "video_url": "https://example.com/background.mp4",
    "start": 0,
    "end": 10
    "volume": 0.8,
    "transition": "fade_in"
})

print(f"Video addition result: {response.json()}")

Create stylized text

import requests

# Add title text
response = requests.post("http://localhost:9001/add_text", json={
    "text": "Welcome to CapCutAPI",
    "start": 0,
    "end": 5,
    "font": "Source Han Sans",read
    "font_color": "#FFD700",
    "font_size": 48,
    "shadow_enabled": True,
    "background_color": "#000000"
})

print(f"Text addition result: {response.json()}")

More examples can be found in the example.py file.

Complete workflow

# 1. Create a new project
draft = mcp_client.call_tool("create_draft", {
    "width": 1080,
    "height": 1920
})
draft_id = draft["result"]["draft_id"]

# 2. Add background video
mcp_client.call_tool("add_video", {
    "video_url": "https://example.com/bg.mp4",
    "draft_id": draft_id,
    "start": 0,
    "end": 10,
    "volume": 0.6
})

# 3. Add title text
mcp_client.call_tool("add_text", {
    "text": "AI-Driven Video Production",
    "draft_id": draft_id,
    "start": 1,
    "end": 6,
    "font_size": 56,
    "shadow_enabled": True,
    "background_color": "#1E1E1E"
})

# 4. Add keyframe animation
mcp_client.call_tool("add_video_keyframe", {
    "draft_id": draft_id,
    "track_name": "main",
    "property_types": ["scale_x", "scale_y", "alpha"],
    "times": [0, 2, 4],
    "values": ["1.0", "1.2", "0.8"]
})

# 5. Save the project
result = mcp_client.call_tool("save_draft", {
    "draft_id": draft_id
})

print(f"Project saved: {result['result']['draft_url']}")

Advanced text effects

# Multi-style colored text
mcp_client.call_tool("add_text", {
    "text": "Colored text effect demonstration",
    "draft_id": draft_id,
    "start": 2,
    "end": 8,
    "font_size": 42,
    "shadow_enabled": True,
    "shadow_color": "#FFFFFF",
    "background_alpha": 0.8,
    "background_round_radius": 20,
    "text_styles": [
        {"start": 0, "end": 2, "font_color": "#FF6B6B"},
        {"start": 2, "end": 4, "font_color": "#4ECDC4"},
        {"start": 4, "end": 6, "font_color": "#45B7D1"}
    ]
})

Calling save_draft will generate a folder starting with dfd_ in the current directory of capcut_server.py. Copy this to the CapCut/Jianying drafts directory to see the generated draft in the application.

You can find a lot of pattern in the pattern directory.

We welcome contributions of all forms! Our iteration rules are:

• No direct PRs to main
• PRs can be submitted to the dev branch
• Merges from dev to main and releases will happen every Monday

If you want to:

• Feedback on issues
• Feature suggestions
• Get latest news

Contact: [email protected]

• Video Production: Want to use this API for batch production of videos? I offer free consulting services to help you use this API. In return, I'll ask for the production workflow template to be open-sourced in the template directory of this project.

• Join us: Our goal is to provide a stable and reliable video editing tool that integrates well with AI-generated images, videos, and audio. If you are interested, submit a PR and I'll see it. For more in-depth involvement, the code for the MCP Editing Agent, web-based editing client, and cloud rendering modules has not been open-sourced yet.

Contact: [email protected]

Made with ❤️ by the CapCutAPI Community