home / mcp / vibeshift mcp server
Provides an automated security analysis and AI-driven remediation loop for AI-assisted coding environments via MCP.
Configuration
View docs{
"mcpServers": {
"groundng-vibeshift": {
"command": "uv",
"args": [
"--directory",
"path/to/cloned_repo",
"run",
"mcp_server.py"
],
"env": {
"LLM_API_KEY": "YOUR_LLM_API_KEY"
}
}
}
}VibeShift exposes security analysis and AI-driven remediation as an MCP service that you can connect to from your AI coding environment. By integrating with your coding assistants, it analyzes AI-generated code for vulnerabilities, runs automated tests, and provides actionable feedback to guide secure development at the moment code is produced.
Use VibeShift to add security analysis directly into your AI-assisted coding workflow. When your AI coding agent generates or significantly changes code, VibeShift performs security checks, returns vulnerability details, and helps your AI assistant suggest or apply fixes. You can trigger recording and testing workflows to capture and validate secure behavior, and you can run a regression test suite to detect reintroduced issues.
Prerequisites before you begin are straightforward. You need Python 3.10 or newer and a working MCP client. You will also need an installed Playwright runtime for test execution.
# Prerequisites
python3 --version
pip --version
# Install MCP client (CLI)
pip install -U mcp[cli]
# Ensure Playwright browsers are installed (for test execution)
pip install -r requirements.txt
patchright install --with-depsSet up your environment and MCP server so your AI coding assistant can communicate with VibeShift.
# .env
LLM_API_KEY="YOUR_LLM_API_KEY"Add the MCP server configuration to enable your MCP client to connect to VibeShift. The server runs as a local process and is controlled via the MCP interface.
{
"mcpServers": {
"vibeshift": {
"command": "uv",
"args": ["--directory","path/to/cloned_repo", "run", "mcp_server.py"]
}
}
}Keep the MCP server running as you interact with your AI coding assistant. You will issue natural language prompts to your AI agent and expect VibeShift to respond with security reports, test artifacts, or remediation guidance.
If you encounter connection issues, verify that the MCP server is running in the expected directory and that the directory path in the configuration matches where your mcp_server.py script resides.
Static code analysis to find vulnerabilities and insecure patterns in source code.
Dynamic scanning for template-based vulnerabilities and exposure checks.
Dynamic analysis for running components to detect runtime security issues.
Automates browser interactions for UI tests and test recordings.
Controls the browser during automated test recording and playback.
Executes recorded test flows and captures results, screenshots, and logs.
Crawls websites to discover pages and generate test step suggestions.
Interacts with the language model to plan steps and interpret results.
Coordinates web interactions and HTML/vision processing for test planning.
Core MCP integration that routes requests, invokes analyzers, records tests, and reports results.