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MCP Code Checker

@MarcusJellinghaus

リポジトリ

基本情報

カテゴリ

開発者ツール

ライセンス

MIT

トランスポート

stdio

作者

MarcusJellinghaus

MCP Code Checker について

MCP server providing code quality checks (pylint and pytest) with smart LLM-friendly prompts for analysis and fixes. Enables Claude and other AI assistants to analyze your code and suggest improvements.

#python#mcp#pytest#pylint#mcp-server

MCP Code Checker 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": {
    "mcp_server_code_checker_python": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

MCP Code Checker 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 MCP Code Checker?

MCP Code Checker is a Model Context Protocol (MCP) server that provides code quality checking operations for Python projects. It enables AI assistants like Claude, VSCode with GitHub Copilot, or other MCP-compatible clients to run pylint, pytest, and mypy checks within a specified project directory.

How to use MCP Code Checker?

Install the server via pip (pip install git+https://github.com/MarcusJellinghaus/mcp-tools-py.git), then run it with the required --project-dir argument. Configure it in your MCP client (e.g., Claude Desktop) using the mcpServers JSON block, pointing either --python-executable or --venv-path to the environment where pytest, pylint, and mypy are installed.

Key features of MCP Code Checker

  • Run pylint checks for code quality issues
  • Run pytest to identify failing tests
  • Run mypy type checking with strict mode
  • Auto-detection of source and test directories from pyproject.toml
  • Structured JSON logging with full call tracking
  • Security: only defined tools can be executed, scoped to project directory

Use cases of MCP Code Checker

  • Automatically check Python code quality during AI-assisted development
  • Run tests and type checks without giving the AI assistant direct shell access
  • Integrate code quality checks into MCP-compatible IDEs like VSCode or Cursor
  • Obtain structured, context-aware feedback for LLMs to act on

よくある質問

1

What is the difference between MCP Code Checker and giving an AI assistant bash access?

MCP Code Checker provides a more focused, secure approach: only pylint, pytest, and mypy can be executed, all operations are scoped to the specified `project_dir`, and results are formatted and size-limited to reduce context load. The server also logs every tool call with parameters, timing, and results.

2

What dependencies does MCP Code Checker require?

The server requires pytest, pylint, and mypy to be installed in the same Python environment. The `--python-executable` or `--venv-path` must point to that environment (typically the tool’s own venv, not the project’s runtime venv).

3

Does MCP Code Checker support non-Python projects?

No. This server covers Python projects only. Support for other languages is planned for separate, dedicated MCP servers.

4

Where are logs stored?

Logs can be written to the console by default or to a structured JSON file using `--log-file`. If not specified, a timestamped log file is created in `project_dir/logs/mcp_tools_py_{timestamp}.log`. Use `--console-only` to disable file logging.

5

How do I configure the server for my project?

The only required argument is `--project-dir`, pointing to the base directory of your project. Optional arguments include `--python-executable`, `--venv-path`, `--test-folder`, `--log-level`, and `--log-file`. Tool-specific parameters (like `target_directories`) can be passed at runtime.

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