Building MCP Servers with Cursor AI: A Complete Guide

Introduction

The Model Context Protocol (MCP) is revolutionising the way AI assistants interact with external tools and services. When combined with Cursor AI's powerful development capabilities, you can create sophisticated MCP servers that seamlessly integrate with platforms like GitHub and Puppeteer. This blog post will guide you through building your own MCP server using Cursor AI and show you how to leverage GitHub and Puppeteer MCPs to provide context-aware, intelligent solutions.

What is MCP?

The Model Context Protocol (MCP) is an open protocol that enables AI assistants to connect with external data sources, APIs, and tools. MCP servers act as intermediaries, allowing AI models to:

Access real-time data from various services

Perform actions through APIs

Understand context better through structured data

Provide more accurate and relevant solutions

Why Build MCP Servers with Cursor AI?

Cursor AI is an exceptional IDE that combines powerful AI assistance with excellent development tools. Here's why it's perfect for building MCP servers:

Intelligent Code Generation: Cursor AI understands your intent and generates code accordingly

Context Awareness: It maintains context throughout your development session

Error Detection: Catches issues early with intelligent linting

Seamless Integration: Works with TypeScript, Python, and other languages commonly used for MCP servers

Setting Up Your MCP Server Project

Prerequisites

Before we begin, ensure you have:

Node.js (v18 or higher) or Python 3.9+

Cursor AI installed

Basic understanding of TypeScript/JavaScript or Python

An understanding of REST APIs

Project Structure

Let's start by creating a basic MCP server structure. In Cursor AI, you can create a new project and let Cursor help you set it up:

1// server.ts - Basic MCP Server Structure
2import { Server } from '@modelcontextprotocol/sdk/server/index.js';
3import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
4
5const server = new Server({
6  name: 'my-mcp-server',
7  version: '1.0.0',
8}, {
9  capabilities: {
10    tools: {},
11    resources: {},
12  },
13});
14
15// Initialize server
16async function main() {
17  const transport = new StdioServerTransport();
18  await server.connect(transport);
19  console.error('MCP Server running on stdio');
20}
21
22main().catch(console.error);

Building Tools for Your MCP Server

MCP servers expose "tools" that AI assistants can call. Here's how to create a tool:

Connecting with GitHub MCP

GitHub MCP provides powerful capabilities for interacting with repositories, issues, pull requests, and more. Here's how to integrate it:

Benefits of GitHub MCP

Repository Analysis: Analyse codebases, understand structure

Issue Management: Track and manage issues contextually

Code Search: Find relevant code across repositories

Collaboration: Understand team workflows and contributions

Connecting with Puppeteer MCP

Puppeteer MCP enables browser automation, which is incredibly useful for web scraping, testing, and interacting with web applications:

Conclusion

Building MCP servers with Cursor AI opens up incredible possibilities for creating intelligent, context-aware assistants. By integrating GitHub and Puppeteer MCPs, you can:

Understand Context Better: Access real-time data from multiple sources

Provide Accurate Solutions: Make informed decisions based on current state

Automate Complex Tasks: Combine multiple tools for powerful workflows

Enhance AI Capabilities: Give AI assistants the tools they need to be truly helpful

The combination of Cursor AI's intelligent development environment with MCP's protocol for external integration creates a powerful ecosystem for building next-generation AI tools.

Start building your MCP server today and unlock the full potential of context-aware AI assistance!