Content
# JianYing MCP - Video Production MCP Server
[](https://python.org)
[](https://modelcontextprotocol.io)
[](LICENSE)
A video production automation tool based on Model Context Protocol (MCP), enabling AI assistants to create professional video content through natural language.
## 🎯 Project Overview
JianYing MCP is a powerful video production automation tool that allows AI to:
- 🎬 **Automatically create JianYing draft projects**
- 🎵 **Intelligently add audio, video, and text materials**
- ✨ **Apply various effects, filters, and animations**
- 🎨 **Automate video editing workflows**
- 📤 **Export as editable JianYing project files**
## 🚀 Core Features
### 📋 Draft Management
- `rules` - Video production specifications
- `create_draft` - Create a new video draft project
- `export_draft` - Export as a JianYing project file
### 🛤️ Track Management
- `create_track` - Create a video/audio/text track
### 🎥 Video Processing
- `add_video_segment` - Add a video segment (local file or URL)
- `add_video_animation` - Add entrance/exit animations
- `add_video_transition` - Add transition effects
- `add_video_filter` - Apply filter effects
- `add_video_mask` - Add mask effects
- `add_video_background_filling` - Background filling
- `add_video_keyframe` - Keyframe animation
### 🎵 Audio Processing
- `add_audio_segment` - Add an audio segment (local file or URL)
- `add_audio_effect` - Audio effects (electric sound, reverb, etc.)
- `add_audio_fade` - Fade-in/fade-out effects
- `add_audio_keyframe` - Audio keyframes
### 📝 Text Processing
- `add_text_segment` - Add a text segment
- `add_text_animation` - Text animation effects
- `add_text_bubble` - Text bubble effects
- `add_text_effect` - Text effects
### 🔧 Utilities
- `parse_media_info` - Parse media file information
- `find_effects_by_type` - Find available effect resources
## 📦 Quick Start
### 1. Install uv
**Windows:**
```bash
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```
**macOS/Linux:**
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
### 2. Clone the project and install dependencies
```bash
git clone https://github.com/your-username/jianying-mcp.git
cd jianying-mcp
uv sync
```
### 3. Configure the MCP client
Using Augment Code as an example, add server configuration in the MCP client:
```json
{
"mcpServers": {
"jianying-mcp": {
"command": "uv",
"args": [
"--directory",
"/your-path/jianying-mcp/jianyingdraft",
"run",
"server.py"
],
"env": {
"SAVE_PATH": "/your-path/draft",
"OUTPUT_PATH": "/your-path/output"
}
}
}
}
```
- SAVE_PATH: Data storage path - stores draft operation data
- OUTPUT_PATH: Export path - generated JianYing draft file storage location
## 🎥 Demo Video
🎬 [Watch the full demo video](https://www.bilibili.com/video/BV1rhe4z1Eu1)
## 🔧 Development Guide
### Debug Mode
Use MCP Inspector for debugging:
```bash
uv run mcp dev jianyingdraft/server.py
```
## 🙏 Acknowledgements
- [Model Context Protocol](https://modelcontextprotocol.io) - Provides a powerful AI integration protocol
- [pyJianYingDraft](https://github.com/GuanYixuan/pyJianYingDraft) - JianYing project file processing library
---
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