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πŸ€–
πŸ€– AI Development Assistant MCP Server

πŸ€– AI Development Assistant MCP Server

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github.com/yeakub108AI & Agents13Updated 86w ago

About πŸ€– AI Development Assistant MCP Server

πŸ€– AI Development Assistant MCP Server is an MCP server offering coding agents tools for planning, review, file reading, and screenshot analysis. Its README describes it as a tutorial demo rather than a production-ready tool.

Key features

  1. 01Generate code architecture plans
  2. 02Analyze UI screenshots
  3. 03Review code from Git diffs
  4. 04Read one or multiple files

Use cases

  1. 01Plan implementation of a new feature
  2. 02Analyze an interface from a screenshot
  3. 03Review code changes
  4. 04Read multiple files for analysis

MCP support

The MCP server exposes tools for code architecture, screenshot analysis, code review, and file reading to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

πŸ€– 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.

πŸ“Έ Screenshot Buddy

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

πŸ” Code Review

Use git diffs to trigger code reviews.

πŸ“„ Read file & Read multiple files

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


πŸš€ 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"
      ]
    }
  }
}

πŸ“˜ 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.


πŸ› οΈ 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.

πŸ“˜ 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.


πŸ“ Project Structure

src/
β”œβ”€β”€ tools/
β”‚   β”œβ”€β”€ architect.ts    # Code structure generator
β”‚   β”œβ”€β”€ screenshot.ts   # Screenshot analysis tool
β”‚   β”œβ”€β”€ fileReader.ts  # read file & read multiple files tool
β”‚   └── codeReview.ts   # Code review tool
β”œβ”€β”€ env/
β”‚   └── keys.ts         # Environment configuration (add your API keys here!)
└── index.ts           # Main entry point

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.