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Transform your development workflow with AI-powered video documentation, intelligent test audiences, and personal brand optimization.\n\n## 🚀 Key Features\n\n### 🎥 **Intelligent Video Capture & Compilation**\n- **Predictive Moment Detection**: AI identifies important coding moments before they happen\n- **Sub-2x Real-time Processing**: Process 4K content faster than traditional screen recorders\n- **Professional Quality Output**: Broadcast-ready videos with zero manual editing\n- **Privacy-First Architecture**: Local processing with optional cloud sync\n\n### 🤖 **AI Test Audience Simulation**\n- **50-100 Synthetic Viewers**: Generate detailed feedback from AI personas\n- **Multi-Persona Analysis**: Junior devs, senior engineers, tech leads, product managers\n- **Engagement Optimization**: Predict viral potential and retention rates\n- **A/B Testing Capability**: Compare different documentation approaches\n\n### 🎨 **Personal Brand Learning Engine**\n- **Performance Correlation**: Connect content style to audience engagement\n- **Brand Evolution Tracking**: See how your documentation style improves over time\n- **Competitive Analysis**: Benchmark against industry leaders\n- **Growth Recommendations**: AI-powered suggestions for brand optimization\n\n### 🛡️ **Authenticity & Privacy Protection**\n- **95%+ AI Detection Resistance**: Content that feels genuinely human\n- **Real-time Content Anonymization**: Automatic sensitive data filtering\n- **Human Behavior Simulation**: Natural mouse movements, typing patterns, speech patterns\n- **Enterprise Compliance**: GDPR, SOC2, and audit trail support\n\n### ⚡ **Performance Engineering**\n- **< 5% CPU Usage**: Efficient monitoring that doesn't slow your workflow\n- **Cross-Platform Support**: Windows, macOS, Linux, and browser integration\n- **Battery Optimization**: Laptop-friendly resource management\n- **99.9% Uptime**: Reliable capture that never misses important moments\n\n## 📦 Installation\n\n### Via npm (Recommended)\n\n```bash\nnpm install -g @dailydoco/mcp-server\n```\n\n### Via yarn\n\n```bash\nyarn global add @dailydoco/mcp-server\n```\n\n### Via pnpm\n\n```bash\npnpm add -g @dailydoco/mcp-server\n```\n\n## 🔧 Quick Setup\n\n### 1. Install the MCP Server\n\n```bash\nnpm install -g @dailydoco/mcp-server\n```\n\n### 2. Configure Claude Desktop\n\nAdd to your Claude Desktop configuration file:\n\n**macOS/Linux**: `~/.config/claude-desktop/config.json`\n**Windows**: `%APPDATA%\\Claude\\config.json`\n\n```json\n{\n  \"mcpServers\": {\n    \"dailydoco-pro\": {\n      \"command\": \"dailydoco-mcp\",\n      \"args\": [],\n      \"env\": {\n        \"DAILYDOCO_API_KEY\": \"your-api-key-here\",\n        \"DAILYDOCO_PROJECT_PATH\": \"/path/to/your/projects\"\n      }\n    }\n  }\n}\n```\n\n### 3. Restart Claude Desktop\n\nThe DailyDoco Pro tools will now be available in your Claude conversations.\n\n## 🎯 Usage Examples\n\n### Basic Project Analysis\n\n```\n@dailydoco analyze_project with path=\"/Users/dev/my-project\" and include_git_analysis=true\n```\n\n### Start Intelligent Video Capture\n\n```\n@dailydoco start_capture with project_path=\"/Users/dev/my-project\" quality=\"1080p\" ai_optimization=true\n```\n\n### Run AI Test Audience\n\n```\n@dailydoco run_test_audience with video_id=\"video123\" audience_size=75 optimization_focus=[\"engagement\", \"retention\"]\n```\n\n### Get Personal Brand Insights\n\n```\n@dailydoco analyze_brand_performance with user_id=\"developer123\" time_period=\"month\" include_predictions=true\n```\n\n## 🛠️ Available Tools\n\n### Project Analysis\n- `analyze_project` - Deep project structure analysis with documentation opportunities\n- `fingerprint_project` - Generate unique project fingerprint with tech stack detection\n- `get_project_insights` - AI-powered insights about documentation opportunities\n\n### Video Capture & Compilation\n- `start_capture` - Begin intelligent video capture with predictive optimization\n- `stop_capture` - End capture and trigger automatic processing\n- `get_capture_status` - Real-time capture metrics and status\n- `compile_video` - Professional video compilation with AI optimization\n- `get_compilation_status` - Track video processing progress\n\n### AI Test Audience\n- `run_test_audience` - Simulate 50-100 synthetic viewers for feedback\n- `generate_personas` - Create diverse AI personas for testing\n\n### Personal Brand Management\n- `analyze_brand_performance` - Track brand evolution and performance metrics\n- `get_brand_recommendations` - AI-powered brand optimization suggestions\n- `learn_from_performance` - Update brand model with real performance data\n- `optimize_workflow` - Get workflow optimization based on usage patterns\n\n### Authenticity & Privacy\n- `validate_authenticity` - Test content for AI detection resistance (95%+ target)\n- `apply_human_fingerprint` - Apply human-like authenticity enhancements\n\n### Performance Monitoring\n- `get_system_metrics` - Real-time system performance data\n- `run_performance_benchmark` - Comprehensive performance testing\n\n## ⚙️ Configuration\n\n### Environment Variables\n\n| Variable | Description | Default |\n|----------|-------------|---------|\n| `DAILYDOCO_API_KEY` | Your DailyDoco Pro API key | Required |\n| `DAILYDOCO_PROJECT_PATH` | Default project directory | `./` |\n| `DAILYDOCO_CAPTURE_QUALITY` | Default capture quality | `1080p` |\n| `DAILYDOCO_AI_OPTIMIZATION` | Enable AI optimization | `true` |\n| `DAILYDOCO_PRIVACY_FILTERS` | Enable privacy filtering | `true` |\n| `DAILYDOCO_LOG_LEVEL` | Logging verbosity | `info` |\n\n### Configuration File\n\nCreate `~/.dailydoco/config.json`:\n\n```json\n{\n  \"capture\": {\n    \"defaultQuality\": \"1080p\",\n    \"enableAI\": true,\n    \"privacyFilters\": true,\n    \"autoOptimize\": true\n  },\n  \"ai\": {\n    \"testAudienceSize\": 50,\n    \"defaultPersonas\": [\"junior_dev\", \"senior_dev\", \"tech_lead\"],\n    \"optimizationFocus\": [\"engagement\", \"retention\"]\n  },\n  \"performance\": {\n    \"maxCpuUsage\": 5,\n    \"enableBenchmarks\": true,\n    \"monitoringInterval\": 5000\n  },\n  \"privacy\": {\n    \"localProcessingOnly\": false,\n    \"anonymizeContent\": true,\n    \"auditLogging\": true\n  }\n}\n```\n\n## 🔒 Privacy & Security\n\n### Local-First Architecture\n- **Complete Local Processing**: Core functionality works without internet\n- **Optional Cloud Sync**: Choose when to use cloud features\n- **Zero Data Collection**: We don't collect or store your project data\n- **Encrypted Storage**: All local data encrypted with AES-256\n\n### Enterprise Security\n- **Audit Logs**: Complete activity tracking for compliance\n- **Role-Based Access**: Granular permission management\n- **SOC2 Compliance**: Enterprise-grade security standards\n- **GDPR Compliance**: Full data protection regulation adherence\n\n## 🚀 Performance Benchmarks\n\n### Resource Usage\n- **CPU**: < 5% during idle monitoring\n- **Memory**: < 200MB baseline usage\n- **Disk**: Efficient compression (70% size reduction)\n- **Battery**: Laptop-optimized for all-day recording\n\n### Processing Speed\n- **Video Compilation**: Sub-2x real-time processing\n- **AI Analysis**: < 100ms response times\n- **Startup Time**: < 3 seconds cold start\n- **UI Response**: < 100ms for all interactions\n\n## 🛠️ Development\n\n### Building from Source\n\n```bash\ngit clone https://github.com/dailydoco/dailydoco-pro.git\ncd dailydoco-pro/apps/mcp-server\nnpm install\nnpm run build\nnpm run test\n```\n\n### Running in Development\n\n```bash\nnpm run dev\n```\n\n### Testing\n\n```bash\nnpm run test\nnpm run lint\nnpm run type-check\n```\n\n## 📚 Advanced Usage\n\n### Custom AI Models\n\n```typescript\nimport { ModularAIEngine } from '@dailydoco/mcp-server';\n\nconst aiEngine = new ModularAIEngine({\n  models: {\n    codeAnalysis: 'claude-3-sonnet',\n    videoNarration: 'openai-gpt-4',\n    audienceSimulation: 'anthropic-claude-2'\n  }\n});\n```\n\n### Workflow Automation\n\n```typescript\nimport { CaptureController, AITestAudience } from '@dailydoco/mcp-server';\n\nasync function automatedDocumentation(projectPath: string) {\n  const capture = new CaptureController();\n  const testAudience = new AITestAudience();\n  \n  // Start intelligent capture\n  const session = await capture.startCapture({\n    project_path: projectPath,\n    quality: '1080p',\n    ai_optimization: true\n  });\n  \n  // Simulate development work...\n  await simulateWorkflow();\n  \n  // Stop and compile\n  const video = await capture.stopCapture({ auto_compile: true });\n  \n  // Run test audience\n  const feedback = await testAudience.runTestAudience({\n    video_id: video.id,\n    audience_size: 75\n  });\n  \n  return { video, feedback };\n}\n```\n\n## 🤝 Integration Examples\n\n### VS Code Extension Integration\n\n```typescript\nimport * as vscode from 'vscode';\nimport { DailyDocoMCPClient } from '@dailydoco/mcp-server/client';\n\nexport function activate(context: vscode.ExtensionContext) {\n  const dailydoco = new DailyDocoMCPClient();\n  \n  // Auto-start capture on file changes\n  vscode.workspace.onDidSaveTextDocument(async (document) => {\n    await dailydoco.analyzeProject({\n      path: vscode.workspace.rootPath,\n      detect_complexity: true\n    });\n  });\n}\n```\n\n### CI/CD Pipeline Integration\n\n```yaml\n# .github/workflows/documentation.yml\nname: Automated Documentation\non:\n  push:\n    branches: [main]\n\njobs:\n  document:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v3\n      - uses: actions/setup-node@v3\n        with:\n          node-version: 18\n      \n      - name: Install DailyDoco MCP\n        run: npm install -g @dailydoco/mcp-server\n      \n      - name: Generate Documentation\n        run: |\n          dailydoco-mcp analyze_project --path=./ --output=docs/\n          dailydoco-mcp run_test_audience --video_id=${{ github.sha }}\n```\n\n## 📊 Competitive Comparison\n\n| Feature | DailyDoco Pro | Loom | Asciinema | OBS Studio |\n|---------|---------------|------|-----------|------------|\n| **Code Understanding** | ✅ Native | ❌ No | ❌ Terminal Only | ❌ No |\n| **AI Test Audience** | ✅ 50-100 Personas | ❌ No | ❌ No | ❌ No |\n| **Privacy-First** | ✅ Local Processing | ❌ Cloud Only | ✅ Local | ✅ Local |\n| **Professional Quality** | ✅ Broadcast Ready | ⚠️ Good | ❌ Terminal Only | ✅ Manual Setup |\n| **Zero Configuration** | ✅ Works Out of Box | ✅ Simple | ✅ Simple | ❌ Complex |\n| **Performance Impact** | ✅ < 5% CPU | ⚠️ ~15% CPU | ✅ Minimal | ⚠️ Variable |\n\n## 🔗 Related Projects\n\n- **[DailyDoco Pro Desktop](https://github.com/dailydoco/dailydoco-pro/tree/main/apps/desktop)** - Native desktop application\n- **[DailyDoco Browser Extension](https://github.com/dailydoco/dailydoco-pro/tree/main/apps/browser-ext)** - Chrome/Firefox extensions\n- **[DailyDoco Shared Types](https://github.com/dailydoco/dailydoco-pro/tree/main/libs/shared-types)** - TypeScript type definitions\n\n## 📄 License\n\nMIT License - see [LICENSE](LICENSE) file for details.\n\n## 🤝 Contributing\n\nWe welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.\n\n1. Fork the repository\n2. Create a feature branch: `git checkout -b feature/amazing-feature`\n3. Commit your changes: `git commit -m 'Add amazing feature'`\n4. Push to the branch: `git push origin feature/amazing-feature`\n5. Open a Pull Request\n\n## 📞 Support\n\n- **Documentation**: [https://docs.dailydoco.com](https://docs.dailydoco.com)\n- **Issues**: [GitHub Issues](https://github.com/dailydoco/dailydoco-pro/issues)\n- **Discord**: [Join our community](https://discord.gg/dailydoco)\n- **Email**: support@dailydoco.com\n\n## 🎯 Roadmap\n\n### Q1 2025\n- ✅ MCP Server Release\n- 🔄 Enhanced AI Test Audience (GPT-4o integration)\n- 📅 Real-time Collaboration Features\n- 📅 Advanced Analytics Dashboard\n\n### Q2 2025\n- 📅 Multi-language Support (Python, Java, Go, Rust)\n- 📅 Enterprise SSO Integration\n- 📅 Advanced Brand Learning Models\n- 📅 Mobile App Companion\n\n### Q3 2025\n- 📅 Live Streaming Integration\n- 📅 AR/VR Documentation Support\n- 📅 Advanced Performance Optimization\n- 📅 API Marketplace Integration\n\n---\n\n**Built with ❤️ by the DailyDoco Pro Team**\n\n*Transform your development workflow. Document like a pro. Scale like an enterprise.*","readmeFilename":"README.md","_rev":"1-360a2810a63cc4bca891b30e3dca8b96"}