QA MCP (Probably will rename to vibecheck?)

@Ilikepizza2

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Basic information

About QA MCP

[MCP Server] The Security Agent for AI assisted coding

#test #web #qa #automation #ai #coding

QA MCP config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "GroundNG-Web-Tester": {
      "command": "uv",
      "args": [
        "--directory",
        "path/to/cloned_repo",
        "run",
        "mcp_server.py"
      ]
    }
  }
}

QA MCP tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is VibeShift?

VibeShift is a security agent that integrates with AI coding assistants via the Model Context Protocol (MCP). It analyzes code generated by AI, identifies vulnerabilities, and facilitates AI-driven remediation before insecure code reaches the codebase. It is designed for developers using tools like Cursor, GitHub Copilot, or Claude Code.

How to use VibeShift?

Install Python 3.10+, clone the repository, create a virtual environment, install dependencies with pip install -r requirements.txt, and install Playwright browsers with patchright install --with-deps. Rename .env.example to .env and add your LLM API key. Add the MCP server configuration to your AI assistant's MCP config. Then interact with VibeShift through natural language commands via your AI coding assistant.

Key features of VibeShift

MCP integration with major AI coding assistants
Automated SAST scanning using Semgrep
Dynamic analysis via Nuclei
AI-assisted test recording and execution
AI-powered test discovery and regression testing
Self‑healing tests that adapt to code changes
Visual regression testing (pixelmatch and LLM)

Use cases of VibeShift

Automatically scan AI‑generated code for security vulnerabilities
Record and run Playwright‑based test scripts from natural language descriptions
Execute regression test suites to catch regressions
Discover test steps by crawling websites and analyzing pages

Frequently asked questions

What are the prerequisites for running VibeShift?

Python 3.10+, an LLM API key (Gemini 2.0 Flash works well), the MCP package installed (`pip install mcp[cli]`), and Playwright browsers installed (`patchright install --with-deps`).

How do I configure VibeShift?

Rename the `.env.example` file to `.env` in the project root and add your LLM API key under the `LLM_API_KEY` variable.

What security tools does VibeShift integrate?

VibeShift uses Semgrep for static code analysis (SAST) and Nuclei for template‑based dynamic scanning (DAST). It also leverages Playwright for browser automation.

Where are test and security results stored?

Recorded tests are saved as JSON files in the `output/` directory. Execution results are returned to the AI assistant and also saved to `output/execution_result_....json`. Discovery results are saved to `output/discovery_results_....json`.

Does VibeShift support UI testing beyond standard Playwright?

Yes, it supports UI tests not natively supported by Playwright, such as checking if text is overflowing in a div.

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