What are the system requirements?
Python 3.6 or higher; no external libraries are needed – only the Python standard library is used.
@kiranimmadi2
基本情報
MCP-Based AI Code Analysis Tool: Enables LLM agents to interact with, analyze, and debug codebases via structured MCP tool calls — scanning project structure, extracting code elements, and detecting Python anti-patterns.
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-kiranimmadi2": {
"command": "python",
"args": [
"mcp.py",
"/path/to/your/project",
"[options]"
]
}
}
}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。
🧠 MCP Code Assistant is an AI‑powered developer tool built on the Model Context Protocol (MCP). It enables LLM agents to scan, analyze, and debug codebases through structured MCP tool calls, exposing project structure, code elements (classes, functions, imports), and Python anti‑pattern detection – without requiring manual context injection.
Clone the repository and run python mcp.py /path/to/your/project with command‑line options such as --scan, --structure, --analyze <file>, --search <regex>, or --bugs. It can also be imported as a Python library (from mcp import MCP) to produce structured outputs for LLM consumption.
Python 3.6 or higher; no external libraries are needed – only the Python standard library is used.
Clone the repository from GitHub (`git clone https://github.com/kiranimmadi2/MCP-Server.git`) and change into the `MCP-Server` directory.
Currently, analysis (extracting classes, functions, imports, and bug detection) is focused on Python files. Support for JavaScript and TypeScript is listed on the roadmap.
The current version exposes functionality via CLI and as a Python library. The roadmap includes implementing full MCP server mode with JSON‑RPC tool registration and LLM agent integration examples.
The project is released under the MIT License.

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