Vedit-MCP
About
Perform basic video editing operations using natural language commands. Requires ffmpeg to be installed.
Details
- Author
- zakahan
- Categories
- Productivity, Other, Media
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Setup
Install Vedit-MCP in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/zakahan/vedit-mcp
Follow the installation instructions in the repository README, then restart your MCP client.
This is an MCP service forvideo editing, which can achieve basic editing operations with just one sentence.
1.1 Clone this project or directly download the zip package
- It is recommended to use uv for installationcd vedit-mcp uv pip install -r requirements.txt
vedit-mcp.pyrelies onffmpegfor implementation. Therefore, please configure ffmpeg.
# For Mac brew install ffmpeg # For Ubuntu sudo apt update sudo apt install ffmpeg
2.1. It is recommended to usegoogle-adkto build your own project
- Please ensure that the path format is at least as follows
- sample
- kb
- raw/test.mp4 // This is the original video you need to process
- Please install the following two dependencies
# # adk-sample pip install requirements # google-adk==0.3.0 # litellm==1.67.2
Currently, this script uses the API of theVolcano Ark Platform, and you can go there to configure it by yourself.
After obtaining the API_KEY, please configure the API_KEY as an environment variable.
export OPENAI_API_KEY="your-api-key"
After this script is executed correctly and ends, a video result file will be generated in kb/result, and a log file will be generated and the result will be output.
If you need secondary development, you can choose to addvedit_mcp.pyto your project for use.
Firstly, please ensure that your Python environment and ffmpeg configuration are correct Configure cline_mcp_settings. json as follows
{ "mcpServers": { "vedit-mcp": { "command": "python", "args": [ "vedit_mcp.py", "--kb_dir", "your-kb-dir-here" ] } } }
2.3. Execute using the stramlit web interface
- It is recommended to use thethinking modelto handle this type of task. Currently, it seems that thethinking modelperforms better in handling this type of task? But no further testing has been conducted, it's just an intuitive feeling.
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