This project provides an example Model Context Protocol (MCP) server for the Cursor IDE, enabling AI-powered development assistance through custom tools. It targets developers seeking to integrate advanced AI capabilities like code architecture planning, UI screenshot analysis, and automated code reviews directly into their workflow. The primary benefit is enhanced productivity and intelligent support within the IDE.

How It Works

The server acts as a bridge between Cursor's MCP interface and custom TypeScript tools. It leverages LLMs (specifically mentioning OpenAI) to process natural language requests and execute predefined functions. The architecture involves a main entry point (index.ts) that registers and manages these tools, allowing Cursor's AI to invoke them via standard input/output communication. This approach facilitates seamless integration of specialized AI functionalities into the IDE.

Quick Start & Requirements

• Install: npm install or yarn install
• Build: npm run build
• Prerequisites: Node.js, npm/yarn, OpenAI API key.
• Cursor Setup: Add a new MCP server in Cursor settings, pointing to the built dist/index.js file.
• Docs: Cursor MCP Documentation: https://docs.cursor.gg/mcp

Highlighted Details

• Code Architect: Generates plans and instructions for coding agents using advanced LLMs.
• Screenshot Buddy: Analyzes UI design screenshots with a composer agent.
• Code Review: Utilizes git diffs to trigger code review processes.
• Configuration: Environment variables for API keys are managed in src/env/keys.ts.

Maintenance & Community

This project is described as a tutorial demo and not production-ready. The author states they likely won't be fixing issues but encourages forking. No specific community channels or roadmap are provided.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Permissive for commercial use and integration with closed-source projects.

Limitations & Caveats

The project is explicitly stated as a tutorial demo and not production-ready, with limited ongoing maintenance or issue resolution expected. It relies on an OpenAI API key, and direct API key storage in source code is discouraged for production environments.