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Ai Develop Assistant MCP Server

@jieshao11

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

jieshao11

投稿者

jieshao11

Ai Develop Assistant MCP Server について

协助AI开发者需求完善、模块设计、技术架构设计的mcp

#ai-develop-assistant#mcp#project-management

Ai Develop Assistant MCP Server 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": {
    "ai-develop-assistant": {
      "command": "uvx",
      "args": [
        "ai-develop-assistant@latest"
      ],
      "env": {
        "MCP_STORAGE_DIR": "/path/to/your/storage"
      }
    }
  }
}

Ai Develop Assistant MCP Server 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。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Ai Develop Assistant?

Ai Develop Assistant is an MCP server that helps developers clarify requirements, design architecture, and export project documentation. It integrates with the Claude Desktop environment and stores data persistently in local files.

How to use Ai Develop Assistant?

Configure the server in the Claude Desktop JSON config file, set the MCP_STORAGE_DIR environment variable, and restart Claude Desktop. Then use its five tools (requirement_clarifier, requirement_manager, architecture_designer, export_final_document, view_requirements_status) to follow a complete project analysis flow.

Key features of Ai Develop Assistant

  • Requirement clarification and management tools
  • Architecture design generation tool
  • Persistent storage with automatic saves
  • Multi-format export (JSON + Markdown)
  • Complete operation history tracking
  • Configurable storage directory via environment variable

Use cases of Ai Develop Assistant

  • Clarifying vague project requirements with structured prompts
  • Managing requirement documents with version history
  • Generating architecture designs for web applications
  • Exporting final project documentation in JSON and Markdown
  • Tracking analysis progress with status viewing tool

よくある質問

1

What kind of projects can Ai Develop Assistant handle?

The README demonstrates a Web AI resource sharing site example, suggesting it handles general software project analysis and architecture design.

2

What are the runtime requirements?

The server runs with Python and is configured via the Claude Desktop `claude_desktop_config.json` file. A test script (`test_optimized_mcp.py`) is provided for validation.

3

Where does the data live?

All data is stored locally in the directory specified by the `MCP_STORAGE_DIR` environment variable (default `./mcp_data`). Files include `requirements.json`, `history.json`, and exported documents.

4

How does it compare to the original version?

Improvements over the original include data persistence, history tracking, document export, real-time status viewing, and flexible storage configuration.

5

What transport or authentication does it use?

The server uses standard Claude Desktop MCP transport (stdio). No authentication is mentioned; it assumes local usage.

コメント

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