@aegntic/dailydoco-mcp-server/README.md

DailyDoco Pro MCP Server - Claude integration for automated documentation with AI test audiences, personal brand learning, and intelligent video compilation

# DailyDoco Pro MCP Server

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A sophisticated Model Context Protocol (MCP) server that brings **DailyDoco Pro's** elite automated documentation capabilities directly to Claude. Transform your development workflow with AI-powered video documentation, intelligent test audiences, and personal brand optimization.

## 🚀 Key Features

### 🎥 **Intelligent Video Capture & Compilation**
- **Predictive Moment Detection**: AI identifies important coding moments before they happen
- **Sub-2x Real-time Processing**: Process 4K content faster than traditional screen recorders
- **Professional Quality Output**: Broadcast-ready videos with zero manual editing
- **Privacy-First Architecture**: Local processing with optional cloud sync

### 🤖 **AI Test Audience Simulation**
- **50-100 Synthetic Viewers**: Generate detailed feedback from AI personas
- **Multi-Persona Analysis**: Junior devs, senior engineers, tech leads, product managers
- **Engagement Optimization**: Predict viral potential and retention rates
- **A/B Testing Capability**: Compare different documentation approaches

### 🎨 **Personal Brand Learning Engine**
- **Performance Correlation**: Connect content style to audience engagement
- **Brand Evolution Tracking**: See how your documentation style improves over time
- **Competitive Analysis**: Benchmark against industry leaders
- **Growth Recommendations**: AI-powered suggestions for brand optimization

### 🛡️ **Authenticity & Privacy Protection**
- **95%+ AI Detection Resistance**: Content that feels genuinely human
- **Real-time Content Anonymization**: Automatic sensitive data filtering
- **Human Behavior Simulation**: Natural mouse movements, typing patterns, speech patterns
- **Enterprise Compliance**: GDPR, SOC2, and audit trail support

### ⚡ **Performance Engineering**
- **< 5% CPU Usage**: Efficient monitoring that doesn't slow your workflow
- **Cross-Platform Support**: Windows, macOS, Linux, and browser integration
- **Battery Optimization**: Laptop-friendly resource management
- **99.9% Uptime**: Reliable capture that never misses important moments

## 📦 Installation

### Via npm (Recommended)

```bash
npm install -g @dailydoco/mcp-server
```

### Via yarn

```bash
yarn global add @dailydoco/mcp-server
```

### Via pnpm

```bash
pnpm add -g @dailydoco/mcp-server
```

## 🔧 Quick Setup

### 1. Install the MCP Server

```bash
npm install -g @dailydoco/mcp-server
```

### 2. Configure Claude Desktop

Add to your Claude Desktop configuration file:

**macOS/Linux**: `~/.config/claude-desktop/config.json`
**Windows**: `%APPDATA%\Claude\config.json`

```json
{
  "mcpServers": {
    "dailydoco-pro": {
      "command": "dailydoco-mcp",
      "args": [],
      "env": {
        "DAILYDOCO_API_KEY": "your-api-key-here",
        "DAILYDOCO_PROJECT_PATH": "/path/to/your/projects"
      }
    }
  }
}
```

### 3. Restart Claude Desktop

The DailyDoco Pro tools will now be available in your Claude conversations.

## 🎯 Usage Examples

### Basic Project Analysis

```
@dailydoco analyze_project with path="/Users/dev/my-project" and include_git_analysis=true
```

### Start Intelligent Video Capture

```
@dailydoco start_capture with project_path="/Users/dev/my-project" quality="1080p" ai_optimization=true
```

### Run AI Test Audience

```
@dailydoco run_test_audience with video_id="video123" audience_size=75 optimization_focus=["engagement", "retention"]
```

### Get Personal Brand Insights

```
@dailydoco analyze_brand_performance with user_id="developer123" time_period="month" include_predictions=true
```

## 🛠️ Available Tools

### Project Analysis
- `analyze_project` - Deep project structure analysis with documentation opportunities
- `fingerprint_project` - Generate unique project fingerprint with tech stack detection
- `get_project_insights` - AI-powered insights about documentation opportunities

### Video Capture & Compilation
- `start_capture` - Begin intelligent video capture with predictive optimization
- `stop_capture` - End capture and trigger automatic processing
- `get_capture_status` - Real-time capture metrics and status
- `compile_video` - Professional video compilation with AI optimization
- `get_compilation_status` - Track video processing progress

### AI Test Audience
- `run_test_audience` - Simulate 50-100 synthetic viewers for feedback
- `generate_personas` - Create diverse AI personas for testing

### Personal Brand Management
- `analyze_brand_performance` - Track brand evolution and performance metrics
- `get_brand_recommendations` - AI-powered brand optimization suggestions
- `learn_from_performance` - Update brand model with real performance data
- `optimize_workflow` - Get workflow optimization based on usage patterns

### Authenticity & Privacy
- `validate_authenticity` - Test content for AI detection resistance (95%+ target)
- `apply_human_fingerprint` - Apply human-like authenticity enhancements

### Performance Monitoring
- `get_system_metrics` - Real-time system performance data
- `run_performance_benchmark` - Comprehensive performance testing

## ⚙️ Configuration

### Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| `DAILYDOCO_API_KEY` | Your DailyDoco Pro API key | Required |
| `DAILYDOCO_PROJECT_PATH` | Default project directory | `./` |
| `DAILYDOCO_CAPTURE_QUALITY` | Default capture quality | `1080p` |
| `DAILYDOCO_AI_OPTIMIZATION` | Enable AI optimization | `true` |
| `DAILYDOCO_PRIVACY_FILTERS` | Enable privacy filtering | `true` |
| `DAILYDOCO_LOG_LEVEL` | Logging verbosity | `info` |

### Configuration File

Create `~/.dailydoco/config.json`:

```json
{
  "capture": {
    "defaultQuality": "1080p",
    "enableAI": true,
    "privacyFilters": true,
    "autoOptimize": true
  },
  "ai": {
    "testAudienceSize": 50,
    "defaultPersonas": ["junior_dev", "senior_dev", "tech_lead"],
    "optimizationFocus": ["engagement", "retention"]
  },
  "performance": {
    "maxCpuUsage": 5,
    "enableBenchmarks": true,
    "monitoringInterval": 5000
  },
  "privacy": {
    "localProcessingOnly": false,
    "anonymizeContent": true,
    "auditLogging": true
  }
}
```

## 🔒 Privacy & Security

### Local-First Architecture
- **Complete Local Processing**: Core functionality works without internet
- **Optional Cloud Sync**: Choose when to use cloud features
- **Zero Data Collection**: We don't collect or store your project data
- **Encrypted Storage**: All local data encrypted with AES-256

### Enterprise Security
- **Audit Logs**: Complete activity tracking for compliance
- **Role-Based Access**: Granular permission management
- **SOC2 Compliance**: Enterprise-grade security standards
- **GDPR Compliance**: Full data protection regulation adherence

## 🚀 Performance Benchmarks

### Resource Usage
- **CPU**: < 5% during idle monitoring
- **Memory**: < 200MB baseline usage
- **Disk**: Efficient compression (70% size reduction)
- **Battery**: Laptop-optimized for all-day recording

### Processing Speed
- **Video Compilation**: Sub-2x real-time processing
- **AI Analysis**: < 100ms response times
- **Startup Time**: < 3 seconds cold start
- **UI Response**: < 100ms for all interactions

## 🛠️ Development

### Building from Source

```bash
git clone https://github.com/dailydoco/dailydoco-pro.git
cd dailydoco-pro/apps/mcp-server
npm install
npm run build
npm run test
```

### Running in Development

```bash
npm run dev
```

### Testing

```bash
npm run test
npm run lint
npm run type-check
```

## 📚 Advanced Usage

### Custom AI Models

```typescript
import { ModularAIEngine } from '@dailydoco/mcp-server';

const aiEngine = new ModularAIEngine({
  models: {
    codeAnalysis: 'claude-3-sonnet',
    videoNarration: 'openai-gpt-4',
    audienceSimulation: 'anthropic-claude-2'
  }
});
```

### Workflow Automation

```typescript
import { CaptureController, AITestAudience } from '@dailydoco/mcp-server';

async function automatedDocumentation(projectPath: string) {
  const capture = new CaptureController();
  const testAudience = new AITestAudience();
  
  // Start intelligent capture
  const session = await capture.startCapture({
    project_path: projectPath,
    quality: '1080p',
    ai_optimization: true
  });
  
  // Simulate development work...
  await simulateWorkflow();
  
  // Stop and compile
  const video = await capture.stopCapture({ auto_compile: true });
  
  // Run test audience
  const feedback = await testAudience.runTestAudience({
    video_id: video.id,
    audience_size: 75
  });
  
  return { video, feedback };
}
```

## 🤝 Integration Examples

### VS Code Extension Integration

```typescript
import * as vscode from 'vscode';
import { DailyDocoMCPClient } from '@dailydoco/mcp-server/client';

export function activate(context: vscode.ExtensionContext) {
  const dailydoco = new DailyDocoMCPClient();
  
  // Auto-start capture on file changes
  vscode.workspace.onDidSaveTextDocument(async (document) => {
    await dailydoco.analyzeProject({
      path: vscode.workspace.rootPath,
      detect_complexity: true
    });
  });
}
```

### CI/CD Pipeline Integration

```yaml
# .github/workflows/documentation.yml
name: Automated Documentation
on:
  push:
    branches: [main]

jobs:
  document:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: 18
      
      - name: Install DailyDoco MCP
        run: npm install -g @dailydoco/mcp-server
      
      - name: Generate Documentation
        run: |
          dailydoco-mcp analyze_project --path=./ --output=docs/
          dailydoco-mcp run_test_audience --video_id=${{ github.sha }}
```

## 📊 Competitive Comparison

| Feature | DailyDoco Pro | Loom | Asciinema | OBS Studio |
|---------|---------------|------|-----------|------------|
| **Code Understanding** | ✅ Native | ❌ No | ❌ Terminal Only | ❌ No |
| **AI Test Audience** | ✅ 50-100 Personas | ❌ No | ❌ No | ❌ No |
| **Privacy-First** | ✅ Local Processing | ❌ Cloud Only | ✅ Local | ✅ Local |
| **Professional Quality** | ✅ Broadcast Ready | ⚠️ Good | ❌ Terminal Only | ✅ Manual Setup |
| **Zero Configuration** | ✅ Works Out of Box | ✅ Simple | ✅ Simple | ❌ Complex |
| **Performance Impact** | ✅ < 5% CPU | ⚠️ ~15% CPU | ✅ Minimal | ⚠️ Variable |

## 🔗 Related Projects

- **[DailyDoco Pro Desktop](https://github.com/dailydoco/dailydoco-pro/tree/main/apps/desktop)** - Native desktop application
- **[DailyDoco Browser Extension](https://github.com/dailydoco/dailydoco-pro/tree/main/apps/browser-ext)** - Chrome/Firefox extensions
- **[DailyDoco Shared Types](https://github.com/dailydoco/dailydoco-pro/tree/main/libs/shared-types)** - TypeScript type definitions

## 📄 License

MIT License - see [LICENSE](LICENSE) file for details.

## 🤝 Contributing

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

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

## 📞 Support

- **Documentation**: [https://docs.dailydoco.com](https://docs.dailydoco.com)
- **Issues**: [GitHub Issues](https://github.com/dailydoco/dailydoco-pro/issues)
- **Discord**: [Join our community](https://discord.gg/dailydoco)
- **Email**: support@dailydoco.com

## 🎯 Roadmap

### Q1 2025
- ✅ MCP Server Release
- 🔄 Enhanced AI Test Audience (GPT-4o integration)
- 📅 Real-time Collaboration Features
- 📅 Advanced Analytics Dashboard

### Q2 2025
- 📅 Multi-language Support (Python, Java, Go, Rust)
- 📅 Enterprise SSO Integration
- 📅 Advanced Brand Learning Models
- 📅 Mobile App Companion

### Q3 2025
- 📅 Live Streaming Integration
- 📅 AR/VR Documentation Support
- 📅 Advanced Performance Optimization
- 📅 API Marketplace Integration

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**Built with ❤️ by the DailyDoco Pro Team**

*Transform your development workflow. Document like a pro. Scale like an enterprise.*