VectCutAPI

Connect AI generates via VectCutAPI Try it online

About this repository (fork notice)

This repository is a fork of the upstream open-source project VectCutAPI by sun-guannan. It contains independent maintenance and local changes and is not an official release from the original authors. Documentation, branding, and product positioning remain with the upstream project and the VectCut community.

• Upstream: https://github.com/sun-guannan/VectCutAPI
• License: Same as upstream — Apache License 2.0. Redistribution must retain copyright notices and license terms as required by Apache 2.0.
• Changes here: Fixes and edits in this fork are maintained by this repo’s contributors and do not imply endorsement by upstream. For the canonical roadmap and reporting issues, prefer the official repository.

If anything here misattributes work or misses required notices, please open an Issue and it will be corrected promptly.

Project Overview

VectCutAPI 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.

Enjoy It! 😀😀😀

中文说明

Advantages

1. API-Powered Editing: Access all powerfull 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.

Demos

MCP, create your own editing Agent

Combine AI-generated images and videos using VectCutAPI

More

Key Features

Feature Module	API	MCP Protocol	Description
Draft Management	✅	✅	Create and save Jianying/CapCut draft files
Video Processing	✅	✅	Import, clip, transition, and apply effects to multiple video formats
Audio Editing	✅	✅	Audio tracks, volume control, sound effects processing
Image Processing	✅	✅	Image import, animation, masks, filters
Text Editing	✅	✅	Multi-style text, shadows, backgrounds, animations
Subtitle System	✅	✅	SRT subtitle import, style settings, time synchronization
Effects Engine	✅	✅	Visual effects, filters, transition animations
Sticker System	✅	✅	Sticker assets, position control, animation effects
Keyframes	✅	✅	Property animation, timeline control, easing functions
Media Analysis	✅	✅	Get video duration, detect format

Quick Start

1. System Requirements

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

2. Installation and Deployment

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

# 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

3. Start the service

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

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

Skill Integration Guide

Skill中文文档 Skill Guide

MCP Integration Guide

MCP 中文文档 • MCP English Guide

1. Client Configuration

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"
      }
    }
  }
}

2. Connection Test

# Test MCP connection
python test_mcp_client.py

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

Usage Examples

1. API Example

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 VectCutAPI",
    "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.

2. MCP Protocol Example

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"}
    ]
})

3. Downloading Drafts

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.

Pattern

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

Community & Support

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

Contact Us

🤝 Collaboration

• Video Production: Want to use this API for batch production of videos with AIGC?

• 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: abelchrisnic@gmail.com

📈 Star History

Made with ❤️ by the CapCutAPI Community