Cursor MCP (Model Context Protocol)

Cursor MCP is a bridge between Claude's desktop application and the Cursor editor, enabling seamless AI-powered automation and multi-instance management. It's part of the broader Model Context Protocol (MCP) ecosystem, allowing Cursor to interact with various AI models and services through standardized interfaces.

Overview

🤖 AI Integration

• Direct integration with Claude's desktop application
• Ability to leverage other MCP-compatible AI services
• Real-time context sharing between AI and editor
• AI-powered automation and code generation

🔌 MCP Protocol Support

• Standardized communication with AI models
• Extensible plugin system for additional MCPs
• Context-aware command execution
• Secure token-based authentication

🖥️ Cross-Platform Window Management

• Seamlessly manage Cursor editor windows across operating systems
• Focus, minimize, restore, and arrange windows programmatically
• Track window state changes and positions
• Handle multiple Cursor instances simultaneously

⌨️ Input Automation

• AI-driven keyboard input with support for:
  • Code generation and insertion
  • Refactoring operations
  • Context-aware completions
  • Multi-cursor editing
• Intelligent mouse automation including:
  • Smart selection
  • Context-menu operations
  • AI-guided navigation

🔄 Process Management

• AI-orchestrated instance management
• Smart workspace organization
• Automatic context preservation
• Intelligent session recovery

MCP Integration

Claude Desktop Integration

import { ClaudeMCP } from 'cursor-mcp/claude'

// Connect to Claude's desktop app
const claude = await ClaudeMCP.connect()

// Execute AI-powered operations
await claude.generateCode({
    prompt: 'Create a React component',
    context: currentFileContent,
    language: 'typescript'
})

// Get AI suggestions
const suggestions = await claude.getSuggestions({
    code: selectedText,
    type: 'refactor'
})

Using Multiple MCPs

import { MCPRegistry } from 'cursor-mcp/registry'

// Register available MCPs
MCPRegistry.register('claude', ClaudeMCP)
MCPRegistry.register('github-copilot', CopilotMCP)

// Use different AI services
const claude = await MCPRegistry.get('claude')
const copilot = await MCPRegistry.get('github-copilot')

// Compare suggestions
const claudeSuggestions = await claude.getSuggestions(context)
const copilotSuggestions = await copilot.getSuggestions(context)

Custom MCP Integration

import { BaseMCP, MCPProvider } from 'cursor-mcp/core'

class CustomMCP extends BaseMCP implements MCPProvider {
    async connect() {
        // Custom connection logic
    }

    async generateSuggestions(context: CodeContext) {
        // Custom AI integration
    }
}

// Register custom MCP
MCPRegistry.register('custom-ai', CustomMCP)

Configuration

The tool can be configured through environment variables or a config file at:

• Windows: %LOCALAPPDATA%\cursor-mcp\config\config.json
• macOS: ~/Library/Application Support/cursor-mcp/config/config.json
• Linux: ~/.config/cursor-mcp/config.json

Example configuration:

{
    "mcp": {
        "claude": {
            "enabled": true,
            "apiKey": "${CLAUDE_API_KEY}",
            "contextWindow": 100000
        },
        "providers": {
            "github-copilot": {
                "enabled": true,
                "auth": "${GITHUB_TOKEN}"
            }
        }
    },
    "autoStart": true,
    "maxInstances": 4,
    "windowArrangement": "grid",
    "logging": {
        "level": "info",
        "file": "cursor-mcp.log"
    }
}

Installation

Windows

# Run as Administrator
Invoke-WebRequest -Uri "https://github.com/your-org/cursor-mcp/releases/latest/download/cursor-mcp-windows.zip" -OutFile "cursor-mcp.zip"
Expand-Archive -Path "cursor-mcp.zip" -DestinationPath "."
.\windows.ps1

macOS

# Run with sudo
curl -L "https://github.com/your-org/cursor-mcp/releases/latest/download/cursor-mcp-macos.zip" -o "cursor-mcp.zip"
unzip cursor-mcp.zip
sudo ./macos.sh

Linux

# Run with sudo
curl -L "https://github.com/your-org/cursor-mcp/releases/latest/download/cursor-mcp-linux.zip" -o "cursor-mcp.zip"
unzip cursor-mcp.zip
sudo ./linux.sh

Usage

Basic Usage

import { CursorInstanceManager } from 'cursor-mcp'

// Get the instance manager
const manager = CursorInstanceManager.getInstance()

// Start a new Cursor instance
await manager.startNewInstance()

// Get all running instances
const instances = await manager.getRunningInstances()

// Focus a specific instance
await manager.focusInstance(instances[0])

// Close all instances
await manager.closeAllInstances()

Window Management

import { WindowManager } from 'cursor-mcp'

const windowManager = WindowManager.getInstance()

// Find all Cursor windows
const windows = await windowManager.findCursorWindows()

// Focus a window
await windowManager.focusWindow(windows[0])

// Arrange windows side by side
await windowManager.arrangeWindows(windows, 'sideBySide')

// Minimize all windows
for (const window of windows) {
    await windowManager.minimizeWindow(window)
}

Input Automation

import { InputAutomationService } from 'cursor-mcp'

const inputService = InputAutomationService.getInstance()

// Type text
await inputService.typeText('Hello, World!')

// Send keyboard shortcuts
if (process.platform === 'darwin') {
    await inputService.sendKeys(['command', 'c'])
} else {
    await inputService.sendKeys(['control', 'c'])
}

// Mouse operations
await inputService.moveMouse(100, 100)
await inputService.mouseClick('left')
await inputService.mouseDrag(100, 100, 200, 200)

How It Works

Bridge Architecture

This tool acts as a middleware layer between Cursor and MCP servers:

1. Cursor Integration:

   • Monitors Cursor's file system events
   • Captures editor state and context
   • Injects responses back into the editor
   • Manages window and process automation

2. MCP Protocol Translation:

   • Translates Cursor's internal events into MCP protocol messages
   • Converts MCP responses into Cursor-compatible actions
   • Maintains session state and context
   • Handles authentication and security

3. Server Communication:

   • Connects to Claude's desktop app MCP server
   • Routes requests to appropriate AI providers
   • Manages concurrent connections to multiple MCPs
   • Handles fallbacks and error recovery

graph LR
    A[Cursor Editor] <--> B[Cursor MCP Bridge]
    B <--> C[Claude Desktop MCP]
    B <--> D[GitHub Copilot MCP]
    B <--> E[Custom AI MCPs]

Example Workflow

1. Code Completion Request:

   // 1. Cursor Event (File Change)
   // When user types in Cursor:
   function calculateTotal(items) {
     // Calculate the total price of items|  <-- cursor position
   
   // 2. Bridge Translation
   const event = {
     type: 'completion_request',
     context: {
       file: 'shopping-cart.ts',
       line: 2,
       prefix: '// Calculate the total price of items',
       language: 'typescript',
       cursor_position: 43
     }
   }
   
   // 3. MCP Protocol Message
   await mcpServer.call('generate_completion', {
     prompt: event.context,
     max_tokens: 150,
     temperature: 0.7
   })
   
   // 4. Response Translation
   // Bridge converts MCP response:
   const response = `return items.reduce((total, item) => {
     return total + (item.price * item.quantity);
   }, 0);`
   
   // 5. Cursor Integration
   // Bridge injects the code at cursor position
   

2. Code Refactoring:

   // 1. Cursor Event (Command)
   // User selects code and triggers refactor command
   const oldCode = `
     if (user.age >= 18) {
       if (user.hasLicense) {
         if (car.isAvailable) {
           rentCar(user, car);
         }
       }
     }
   `
   
   // 2. Bridge Translation
   const event = {
     type: 'refactor_request',
     context: {
       selection: oldCode,
       command: 'simplify_nesting'
     }
   }
   
   // 3. MCP Protocol Message
   await mcpServer.call('refactor_code', {
     code: event.context.selection,
     style: 'simplified',
     maintain_logic: true
   })
   
   // 4. Response Translation
   const response = `
     const canRentCar = user.age >= 18 
       && user.hasLicense 
       && car.isAvailable;
     
     if (canRentCar) {
       rentCar(user, car);
     }
   `
   
   // 5. Cursor Integration
   // Bridge replaces selected code
   

3. Multi-File Context:

   // 1. Cursor Event (File Dependencies)
   // When user requests help with a component
   
   // 2. Bridge Translation
   const event = {
     type: 'context_request',
     files: {
       'UserProfile.tsx': '...',
       'types.ts': '...',
       'api.ts': '...'
     },
     focus_file: 'UserProfile.tsx'
   }
   
   // 3. MCP Protocol Message
   await mcpServer.call('analyze_context', {
     files: event.files,
     primary_file: event.focus_file,
     analysis_type: 'component_dependencies'
   })
   
   // 4. Response Processing
   // Bridge maintains context across requests
   

Integration Methods

1. File System Monitoring:

   import { FileSystemWatcher } from 'cursor-mcp/watcher'
   
   const watcher = new FileSystemWatcher({
     paths: ['/path/to/cursor/workspace'],
     events: ['change', 'create', 'delete']
   })
   
   watcher.on('change', async (event) => {
     const mcpMessage = await bridge.translateEvent(event)
     await mcpServer.send(mcpMessage)
   })
   

2. Window Integration:

   import { CursorWindow } from 'cursor-mcp/window'
   
   const window = new CursorWindow()
   
   // Inject AI responses
   await window.injectCode({
     position: cursorPosition,
     code: mcpResponse.code,
     animate: true  // Smooth typing animation
   })
   
   // Handle user interactions
   window.onCommand('refactor', async (selection) => {
     const mcpMessage = await bridge.createRefactorRequest(selection)
     const response = await mcpServer.send(mcpMessage)
     await window.applyRefactoring(response)
   })
   

3. Context Management:

   import { ContextManager } from 'cursor-mcp/context'
   
   const context = new ContextManager()
   
   // Track file dependencies
   await context.addFile('component.tsx')
   await context.trackDependencies()
   
   // Maintain conversation history
   context.addMessage({
     role: 'user',
     content: 'Refactor this component'
   })
   
   // Send to MCP server
   const response = await mcpServer.send({
     type: 'refactor',
     context: context.getFullContext()
   })
   

Security

• Secure token-based authentication for AI services
• Encrypted communication channels
• Sandboxed execution environment
• Fine-grained permission controls

Requirements

Windows

• Windows 10 or later
• Node.js 18 or later
• Administrator privileges for installation

macOS

• macOS 10.15 (Catalina) or later
• Node.js 18 or later
• Xcode Command Line Tools
• Accessibility permissions for Terminal

Linux

• X11 display server
• Node.js 18 or later
• xdotool
• libxtst-dev
• libpng++-dev
• build-essential

Development

Setup

# Clone the repository
git clone https://github.com/your-org/cursor-mcp.git
cd cursor-mcp

# Install dependencies
npm install

# Build the project
npm run build

# Run tests
npm test

Running Tests

# Run all tests
npm test

# Run specific test suite
npm test -- window-management

# Run with coverage
npm run test:coverage

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• 📚 Documentation
• 🐛 Issue Tracker
• 💬 Discussions
• 🔒 Security

Acknowledgments

• Cursor Editor - The AI-first code editor
• Claude AI - Advanced AI assistant
• @nut-tree/nut-js - Cross-platform automation
• active-win - Window detection