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QA MCP (Probably will rename to vibecheck?)

@Ilikepizza2

リポジトリホームページ

基本情報

カテゴリ

その他

ライセンス

Apache-2.0

トランスポート

stdio

作者

Ilikepizza2

QA MCP について

[MCP Server] The Security Agent for AI assisted coding

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

QA MCP の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

QA MCP のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

1

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`).

2

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.

3

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.

4

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`.

5

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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