![Browser[X]MCP Banner](assets/logo/browserx-mcp-logo-banner.png)

**AI-Powered Browser Automation with Advanced Form Testing**

![License](https://img.shields.io/badge/license-MIT-blue.svg)
![Node.js](https://img.shields.io/badge/node-%3E%3D18.0.0-brightgreen.svg)
![Version](https://img.shields.io/badge/version-1.0.0--beta.1-orange.svg)
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Browser[X]MCP is a Model Context Provider (MCP) server that enables AI-driven browser automation with advanced form testing capabilities, intelligent element extraction, and comprehensive interaction logging.

**Connect your AI apps to browser automation** - Works seamlessly with Cursor, Claude Desktop, VS Code, and other MCP-compatible applications.

## ✨ Features

### 🤖 **AI-Driven Testing**
- **Smart Form Filling**: AI automatically fills forms with realistic test data
- **Batch Actions**: Efficient bulk operations for multiple elements (up to 5 actions per batch)
- **Context Awareness**: AI understands page state and avoids redundant actions
- **Loop Detection**: Prevents infinite testing cycles

### ⚡ **Batch Operations System**
- **Multi-Element Processing**: Execute up to 5 actions simultaneously
- **Intelligent Grouping**: AI automatically groups similar elements for batch processing
- **Performance Optimization**: Reduce API calls and execution time by 3-5x
- **Error Isolation**: Individual action failures don't stop the entire batch
- **Smart Prioritization**: Batch similar input types (text fields, checkboxes, etc.)

### 🎯 **Advanced Element Extraction**
- **XML Canvas Format**: Compact, efficient page representation (800x+ compression)
- **ID-Based Targeting**: Reliable element identification
- **Coordinate Mapping**: Precise click positioning
- **Real-time Updates**: Dynamic page state tracking

### 💰 **Token Economics & Cost Efficiency**
- **Massive Token Savings**: 800x+ data compression vs screenshots
- **AI Cost Reduction**: ~90% lower AI API costs compared to vision models
- **Text vs Vision Models**: Use cheaper text models instead of expensive vision APIs
- **Scalable Operations**: Process thousands of pages at fraction of screenshot costs
- **Performance Boost**: 10x faster processing with compact data format

### 📊 **Comprehensive Logging**
- **Action History**: Detailed logs of all AI decisions and actions
- **Form Data Capture**: Real-time extraction of filled form data
- **Performance Metrics**: Success rates, timing, and efficiency stats
- **Test Reports**: JSON and console output formats

### 🛡️ **Robust Automation**
- **Field Clearing**: Advanced input field cleaning before entry
- **File Upload Handling**: Programmatic file upload without OS dialogs
- **Error Recovery**: Graceful handling of failed operations
- **Stealth Mode**: Reduced bot detection signatures

## 🚀 Quick Start

### Installation

```bash
# Clone the repository
git clone https://github.com/rnd-pro/browser-x-mcp.git
cd browser-x-mcp

# Install dependencies
npm install

# Install Playwright browser binaries for local browser tests
npx playwright install chromium

# Configure environment
cp .env.example .env
# Edit .env with your API keys

# Start the MCP server
npm start
```

### Basic Usage

```bash
# Run AI-powered form testing
npm test

# Run with mock AI (faster testing)  
npm run test:mock

# Generate test reports
npm run test:report
```

## 🏗️ Architecture

```
┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   AI Test       │───▶│   MCP Server     │───▶│   Browser       │
│   Agent         │    │   (BrowserX)     │    │   (Playwright)  │
└─────────────────┘    └──────────────────┘    └─────────────────┘
         │                        │                       │
         ▼                        ▼                       ▼
┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Test Reports  │    │   Action Logs    │    │   Screenshots   │
│   & Metrics     │    │   & Form Data    │    │   & Canvas      │
└─────────────────┘    └──────────────────┘    └─────────────────┘
```

## 📁 Project Structure

```
browserx-mcp/
├── src/
│   ├── server/              # MCP Server implementation
│   │   ├── index.js         # Main server with browser automation
│   │   ├── atomic-navigation.js  # Navigation utilities
│   │   └── daemon.js        # Server daemon
│   └── extractor/           # Page analysis tools
│       └── VirtualCanvasExtractor.js  # XML canvas extraction
├── test/
│   ├── ai-mcp-interaction-test.js  # AI-powered testing
│   ├── real-websites-test.js       # Real website validation
│   └── input-types-test-page.html  # Test page
├── tools/                   # Development utilities
│   └── screenshot-analyzer/ # Screenshot analysis tools (planned)
├── examples/                # Usage examples
├── docs/                    # Documentation
└── config/                  # Configuration files
```

## 💰 Cost Efficiency Analysis

### Token Usage Comparison

| Approach | Data Size | Tokens | Cost/Request | 
|----------|-----------|--------|--------------|
| **Screenshots** | 200KB | ~400,000 | $0.0048 |
| **XML Canvas** | 0.25KB | ~500 | $0.0001 |
| **Savings** | **800x smaller** | **800x fewer** | **48x cheaper** |

### Real-World Performance
- **Google Search**: 276KB screenshot → 3KB canvas = **92x compression**
- **GitHub Pages**: 166KB screenshot → 121KB canvas = **1.4x compression** 
- **Average Savings**: **~90% cost reduction** on AI API calls

## 🎮 Usage Examples

### AI-Powered Form Testing

```javascript
import { MCPAIInteractionAgent } from './test/ai-mcp-interaction-test.js';

const agent = new MCPAIInteractionAgent({
    maxIterations: 20,
    useMockAI: false,
    stopOnFailure: true
});

await agent.init();
await agent.runInteractionTest();
const report = await agent.generateReport();
```

### Batch Operations Example

```javascript
// Execute multiple actions in one batch
const batchResponse = await fetch('http://localhost:3001', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
        jsonrpc: '2.0',
        method: 'batch_actions',
        params: {
            actions: [
                { action: 'input_text', element_id: 'email', text: 'user@example.com' },
                { action: 'input_text', element_id: 'password', text: 'SecurePass123' },
                { action: 'click_element_by_id', element_id: 'submit-btn' }
            ]
        },
        id: 1
    })
});
```

### Custom MCP Operations

```javascript
// Connect to MCP server
const response = await fetch('http://localhost:3001', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
        jsonrpc: '2.0',
        method: 'extract_xml_canvas',
        params: {},
        id: 1
    })
});
```

## 🤖 AI Editor Integration

### Works with Popular AI Applications

Browser[X]MCP integrates seamlessly with MCP-compatible AI applications:

| Application | Support | Setup |
|-------------|---------|-------|
| **Cursor** | ✅ Full | Add to `.cursor/mcp.json` |
| **Claude Desktop** | ✅ Full | Add to MCP configuration |
| **VS Code** | ✅ Full | Use MCP extension |
| **Windsurf** | ✅ Full | MCP server integration |

### Cursor Integration

To use Browser[X]MCP with Cursor, add this to your `.cursor/mcp.json`:

```json
{
  "mcpServers": {
    "browser-x-mcp": {
      "command": "node",
      "args": ["./src/server/daemon.js"],
      "env": {
        "BROWSER_X_MCP_DEBUG": "true",
        "NODE_ENV": "development"
      }
    }
  }
}
```

Then restart Cursor and start automating your browser with AI! 🚀

## 🔧 Configuration

### Environment Variables

Create a `.env` file based on `.env.example`:

```bash
# Copy the example file
cp .env.example .env

# Edit with your settings
nano .env
```

Required environment variables:
```bash
# AI Configuration (required for AI testing)
OPENROUTER_API_KEY=your_openrouter_api_key_here
OPENROUTER_MODEL=deepseek/deepseek-r1:free

# Server Configuration
MCP_PORT=3001
BROWSER_HEADLESS=false
```

**Note**: Get your OpenRouter API key from [openrouter.ai](https://openrouter.ai/)

### Test Configuration

```javascript
const config = {
    maxIterations: 30,
    stopOnFailure: true,
    useMockAI: false,
    headless: false,
    loopThreshold: 2
};
```

## 📊 Test Reports

Browser[X]MCP generates comprehensive test reports:

```json
{
  "testMetadata": {
    "testType": "MCP AI-Powered Form Interaction Test",
    "timestamp": "2025-01-20T19:30:22.508Z",
    "duration": "45.2 seconds",
    "model": "deepseek/deepseek-r1:free"
  },
  "results": {
    "totalActions": 12,
    "successfulActions": 12,
    "failedActions": 0,
    "successRate": "100.00%",
    "aiDecisions": [...]
  }
}
```

## 🛠️ Development

### Running Tests

```bash
# AI-powered form testing
npm test

# Alternative AI test command
npm run test:ai

# Mock AI testing (faster, no API required)
npm run test:mock

# View test page manually
npm run test:page
```

### Adding New Features

1. **Server Extensions**: Add new MCP methods in `src/server/index.js`
2. **AI Capabilities**: Enhance AI logic in `test/ai-mcp-interaction-test.js`
3. **Extractors**: Create new page analyzers in `src/extractor/`

## 🗺️ Roadmap

### 🎯 **Planned Features**

#### 🖼️ **Screenshot Analysis Tools**
- Visual element detection and coordinate mapping
- Cropped screenshot analysis for targeted interactions
- AI-powered click coordinate determination
- Visual regression testing capabilities

#### 🧠 **Enhanced AI Integration**
- Multi-model AI support (GPT-4, Claude, Local models)
- Custom AI prompt templates
- Learning from user interactions
- Adaptive testing strategies

#### 🌐 **Extended Browser Support**
- Multi-browser testing (Chrome, Firefox, Safari)
- Browser profile management
- Existing browser connection support
- Extension-based automation

#### 🔍 **Advanced Analysis**
- Performance monitoring and optimization
- Accessibility testing integration
- SEO analysis capabilities
- Security vulnerability scanning

#### 📱 **Cross-Platform Support**
- Mobile browser automation
- Responsive design testing
- Touch interaction simulation
- Device emulation

### 🚀 **Priority Features**
- [ ] Screenshot analyzer tool implementation
- [ ] Enhanced error handling and recovery
- [ ] Performance optimization
- [ ] Comprehensive documentation

### 🎨 **Future Vision**
- [ ] Visual testing framework
- [ ] Multi-browser orchestration
- [ ] Cloud deployment options
- [ ] Enterprise features

## 🤝 Contributing

We welcome contributions! Please see our [Contributing Guide](docs/CONTRIBUTING.md) for details.

### Development Setup

```bash
git clone https://github.com/rnd-pro/browser-x-mcp.git
cd browser-x-mcp
npm install
npm run dev
```

### Submitting Changes

1. Fork the repository
2. Create a feature branch: `git checkout -b feature/amazing-feature`
3. Commit changes: `git commit -m 'Add amazing feature'`
4. Push to branch: `git push origin feature/amazing-feature`
5. Open a Pull Request

## 📝 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.



## 👥 Development Team

**Developed by RND-PRO Team**
- 🌐 Website: [rnd-pro.com](https://rnd-pro.com)
- 💼 Professional development team specializing in innovative automation solutions
- 🤖 Experts in AI integration and browser automation technologies

## 🙏 Acknowledgments

- Built on top of Playwright for reliable browser automation
- Inspired by the MCP (Model Context Provider) specification
- AI integration powered by OpenRouter and various LLM providers
- Similar to [Browser MCP](https://browsermcp.io/) but with advanced AI testing capabilities

## 📞 Support

- 📧 **Issues**: [GitHub Issues](https://github.com/rnd-pro/browser-x-mcp/issues)
- 💬 **Discussions**: [GitHub Discussions](https://github.com/rnd-pro/browser-x-mcp/discussions)
- 📖 **Documentation**: [Repository docs](docs/)

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**Made with ❤️ by RND-PRO Team for the AI automation community**