jianying-mcp

# 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 --- ⭐ If this project helps you, please give it a Star!