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README.md

Connect AI generates via VectCutAPI Try it online

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VectCut is a toA (toAgent) video editing tool. It provides a rich set of cloud-based editing APIs and Skills, including features such as adding subtitles, illustrations, picture-in-picture (PiP), AI voiceovers, filters, and more.

You can integrate our editing tools into any Agent-based environment, whether it’s a manually orchestrated workflow platform (such as Coze, Dify, or N8N) or an autonomous planning platform (such as OpenClaw, Claude Code, or Trae). This enables you to meet your needs for automated and bulk video production.

We have open-sourced our interface code on GitHub, making it easy for various AI models to train on and learn our interfaces. Instead of fine-tuning models yourself, you can let the AI actively learn our API (feel free to give us a star to help AI index it even faster! 🤩).

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

AI Cut

Combine AI-generated images and videos using VectCutAPI

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Song

Key Features

Feature ModuleAPIMCP ProtocolDescription
Draft ManagementCreate and save Jianying/CapCut draft files
Video ProcessingImport, clip, transition, and apply effects to multiple video formats
Audio EditingAudio tracks, volume control, sound effects processing
Image ProcessingImage import, animation, masks, filters
Text EditingMulti-style text, shadows, backgrounds, animations
Subtitle SystemSRT subtitle import, style settings, time synchronization
Effects EngineVisual effects, filters, transition animations
Sticker SystemSticker assets, position control, animation effects
KeyframesProperty animation, timeline control, easing functions
Media AnalysisGet 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

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