Cursor를 위한 Model Context Protocol (MCP) 서버로 설계된 AI 전원 개발 툴킷에 오신 것을 환영합니다! 이 프로젝트는 사용자 정의 AI 도구를 통해 지능형 코딩 지원을 제공합니다. 이것은 주로 튜토리얼 데모이며, 생산 관련 도구가 아닙니다.

✨ 특징

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LLMs를 호출하여 코딩 에이전트에 대한 계획 및 지침을 생성합니다.

# # # # # # # # #

UI 디자인 스크린 샷을 가져 와서 작곡가 에이전트와 함께 사용하십시오.

Physics Code 리뷰

git diffs를 사용하여 트리거 코드 리뷰.

읽기 파일 및 여러 파일을 읽으십시오

단일 파일 읽기는 효율적인 데이터 분석이 가능합니다. 다중 파일 읽기는 대량 데이터 처리가 가능합니다.

⭐ 시작하기

# # 1 환경 설정

먼저 환경 변수를 설정해야 합니다. 파일 만들기 src/env/keys.ts:

⚠️Security Note: 소스 코드에서 API 키를 직접 저장하는 것은 생산 환경에 권장되지 않습니다. 지역 개발 및 학습 목적으로만 사용됩니다. Cursor MCP 인터페이스에서 env var 인라인을 설정할 수 있습니다.

##2. 설치

##3. 서버 구축

##4. 오픈 윈드 서핑 채팅 및 MCP 구성

🤖 AI Development Assistant MCP Server

Welcome to your AI-powered development toolkit, designed as a Model Context Protocol (MCP) server for Cursor! This project provides intelligent coding assistance through custom AI tools. Note that this is mostly a tutorial demo, and not a production-ready tool.

✨ Features

🎨 Code Architect

Call advanced reasoning LLMs to generate plans and instructions for coding agents.

📸 Screenshot Buddy

Take UI design screenshots and use them with the composer agent.

🔍 Code Review

Use git diffs to trigger code reviews.

📄 Read file & Read multiple files

Single-file reading enables efficient data analysis; multi-file reading facilitates bulk data processing.

🚀 Getting Started

1. Environment Setup

First, you’ll need to set up your environment variables. Create a file at src/env/keys.ts:

export const OPENAI_API_KEY = "your_key_here";
// Add any other keys you need

⚠️ Security Note: Storing API keys directly in source code is not recommended for production environments. This is only for local development and learning purposes. You can set the env var inline in the Cursor MCP interface as well.

2. Installation

npm install
# or
yarn install

3. Build the Server

npm run build

4. Open Windsurf Chat and Configure MCP

This project is designed to be used as an MCP server in Cursor. Here’s how to set it up:

1. Open Windsurf on your system.
2. Navigate to the Chat section.
3. Click + Configure MCP (this allows you to add a new MCP server).
4. Add the following JSON configuration:

{
  "mcpServers": {
    "mcp-server": {
      "command": "node",
      "args": [
        "D:\\mpc-server\\build\\index.js"
      ]
    }
  }
}

📘 Pro Tip: You might need to use the full path to your project’s built index.js file.

After adding the server, you should see your tools listed under “Available Tools”. If not, try clicking the refresh button in the top right corner of the MCP server section.

For more details about MCP setup, check out the Windsurf MCP Documentation.

🛠️ Using the Tools

Once configured, you can use these tools directly in Cursor’s Composer. The AI will automatically suggest using relevant tools, or you can explicitly request them by name or description.

For example, try typing in Composer:

• “Review this code for best practices”
• “Help me architect a new feature”
• “Analyze this UI screenshot”
• “Read single file & Read multiple files”

The agent will ask for your approval before making any tool calls.

📘 Pro Tip: You can update your .cursorrules file with instructions on how to use the tools for certain scenarios, and the agent will use the tools automatically.

📁 Project Structure

src/
├── tools/
│   ├── architect.ts    # Code structure generator
│   ├── screenshot.ts   # Screenshot analysis tool