Install
$ agentstack add mcp-zakahan-vedit-mcp ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Vedit-MCP
This is an MCP service for video editing, which can achieve basic editing operations with just one sentence.
English | [中文](README_CN.md)
Quick Start
1. Install Dependencies
1.1 Clone this project or directly download the zip package
1.2 Configure the Python environment
- It is recommended to use uv for installation
cd vedit-mcp
uv pip install -r requirements.txt
- Or install directly using pip
pip install -r requirements.txt
1.3 Configure ffmpeg
vedit-mcp.py relies on ffmpeg for implementation. Therefore, please configure ffmpeg.
# For Mac
brew install ffmpeg
# For Ubuntu
sudo apt update
sudo apt install ffmpeg
2. Start the Service
2.1. It is recommended to use google-adk to build your own project
- Please refer to [adk-sample](sample/adk_sample.py)
Before executing this sample script
- 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 > - adksample.py > - veditmcp.py
- Please install the following two dependencies
# # adk-sample pip install requirements
# google-adk==0.3.0
# litellm==1.67.2
- Please set the api-key and api-base
Currently, this script uses the API of the Volcano Ark Platform, and you can go there to configure it by yourself.
After obtaining the APIKEY, please configure the APIKEY as an environment variable.
export OPENAI_API_KEY="your-api-key"
- Execute the script
cd sample
python adk_sample.py
- End of execution
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 add vedit_mcp.py to your project for use.
2.2 Or build using cline
Firstly, please ensure that your Python environment and ffmpeg configuration are correct Configure clinemcpsettings. 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
To be supplemented
3. precautions
- It is recommended to use the
thinking 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.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: zakahan
- Source: zakahan/vedit-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.