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🚀 Ultimate Developer Productivity Suite - 11 specialized MCP servers for AI-powered code analysis, security scanning, b
Ultimate Developer Productivity Suite - A comprehensive platform built around 11 specialized MCP (Model Context Protocol) servers, providing AI-powered code analysis, security scanning, browser automation, and intelligent workflow orchestration.
┌─────────────────────────────────────────────────────────────┐
│ Frontend (React + TS) │
├─────────────────────────────────────────────────────────────┤
│ FastAPI Backend │
├─────────────────────────────────────────────────────────────┤
│ MCP Server Layer │
├─────────────────────────────────────────────────────────────┤
│ PostgreSQL │ Redis │ Docker │ Kubernetes │
└─────────────────────────────────────────────────────────────┘
| Server | Purpose | Key Features |
|---|---|---|
| kiro-tools | Core Operations | Filesystem, Git, Database operations |
| groq-llm | AI Processing | Ultra-fast Llama 3.1 AI processing |
| openrouter-llm | Multi-Model AI | Access to multiple AI models |
| browser-automation | Web Control | Real browser automation |
| deep-research | Intelligence | Comprehensive web research |
| api-key-sniffer | Security | API key protection and monitoring |
| network-analysis | Monitoring | Network performance analysis |
| enhanced-filesystem | File Ops | Advanced file operations |
| enhanced-git | Version Control | Git analysis and automation |
| real-browser | Web Testing | No-simulation browser control |
| simple-warp | Terminal | Terminal integration and automation |
🎯 Faz 0: Stabilizasyon Tamamlandı! Tek komutla tüm sistemi başlatabilirsiniz.
git clone https://github.com/turtir-ai/mcp-ecosystem-platform.git
cd mcp-ecosystem-platform
# Edit .env with your API keys (optional for basic testing)
# Then start everything with one command:
python start-dev.py
That's it! 🎉 The script will:
| Service | Port | URL |
|---|---|---|
| Frontend | 3000 | http://localhost:3000 |
| Backend API | 8001 | http://localhost:8001 |
| MCP Manager | 8009 | http://localhost:8009 |
git clone https://github.com/turtir-ai/mcp-ecosystem-platform.git
cd mcp-ecosystem-platform
# Copy environment template
cp .env.example .env
# Edit .env with your API keys
cd backend
python -m venv venv
# Windows
venv\Scripts\activate
# Linux/Mac
source venv/bin/activate
pip install -r requirements.txt
cd frontend
npm install
# Terminal 1: Backend
cd backend
uvicorn app.main:app --reload --port 8001
# Terminal 2: Frontend
cd frontend
npm start
# Terminal 3: MCP Manager
python mock-api-server.py
mcp-ecosystem-platform/
├── 📁 backend/ # FastAPI backend
│ ├── 📁 app/
│ │ ├── 📁 core/ # Core interfaces and config
│ │ ├── 📁 services/ # Business logic services
│ │ ├── 📁 api/ # API routes
│ │ ├── 📁 models/ # Database models
│ │ └── 📄 main.py # FastAPI application
│ ├── 📁 tests/ # Backend tests
│ ├── 📄 requirements.txt # Python dependencies
│ └── 📄 Dockerfile # Backend container
├── 📁 frontend/ # React frontend
│ ├── 📁 src/
│ │ ├── 📁 components/ # React components
│ │ ├── 📁 pages/ # Page components
│ │ ├── 📁 services/ # API clients
│ │ └── 📁 types/ # TypeScript types
│ ├── 📄 package.json # Node dependencies
│ └── 📄 Dockerfile.dev # Frontend container
├── 📁 mcp-servers/ # MCP server configurations
├── 📁 vscode-extension/ # VS Code extension
├── 📄 docker-compose.yml # Development environment
├── 📄 .env.example # Environment template
└── 📄 README.md # This file
# API Keys
GROQ_API_KEY=your_groq_api_key
OPENROUTER_API_KEY=your_openrouter_key
GOOGLE_API_KEY=your_google_key
BRAVE_SEARCH_API_KEY=your_brave_key
# Database
DATABASE_URL=postgresql://postgres:password@localhost:5432/mcp_platform
REDIS_URL=redis://localhost:6379/0
# Security
SECRET_KEY=your_secret_key
JWT_SECRET=your_jwt_secret
The platform automatically discovers and configures MCP servers from your .kiro/settings/mcp.json file.
cd backend
pytest tests/ -v --cov=app
cd frontend
npm test
# Run full test suite
docker-compose -f docker-compose.test.yml up --build
# Build and start production containers
docker-compose -f docker-compose.prod.yml up -d
# Deploy to Kubernetes
kubectl apply -f k8s/
/health endpoint for all services/metricsgit checkout -b feature/amazing-feature)git commit -m 'Add amazing feature')git push origin feature/amazing-feature)MCP Ecosystem Platform, AI destekli proaktif sistem yönetimi sunar. AI, sistem sağlığını sürekli izler ve sorunları otomatik olarak tespit ederek çözüm önerileri sunar.
AI sistemi şu bileşenleri sürekli izler:
AI, şu pattern'leri otomatik olarak tespit eder:
Tespit edilen sorunlar için AI şu eylemleri önerebilir:
Web arayüzünde AI destekli özellikler:
AI'ın sistem üzerindeki yetkileri katı güvenlik kurallarıyla sınırlandırılmıştır:
# AI İzin Seviyeleri
SAFE: # Otomatik onaylı
- get_system_health
- mcp_server_logs (INFO/ERROR)
MEDIUM: # Kullanıcı onayı gerekli
- auto_fix_apply
- config_changes
HIGH: # Açık onay gerekli
- mcp_server_restart
- mcp_server_stop
CRITICAL: # Yasaklı
- system_shutdown
- database_delete
1. AI, groq-llm sunucusunun offline olduğunu tespit eder
2. Kullanıcıya "Server Restart" önerisi sunar
3. Kullanıcı onayladıktan sonra sunucuyu yeniden başlatır
4. Başarılı restart sonrası sistem durumunu doğrular
1. AI, %85 CPU kullanımı tespit eder
2. Süreç analizi yaparak kaynak tüketen uygulamaları bulur
3. Optimizasyon önerileri sunar
4. Gerekirse servis yeniden başlatma önerir
1. AI, 200ms+ veritabanı gecikmesi tespit eder
2. Bağlantı havuzu durumunu analiz eder
3. Sorgu optimizasyonu önerileri sunar
4. Gerekirse veritabanı bakım önerir
AI sistemi şu metrikleri takip eder:
AI davranışı .kiro/steering/ai-permissions.md dosyasıyla yapılandırılabilir:
# AI Risk Toleransı
risk_tolerance: "medium"
# Otomatik Onay Ayarları
auto_approve_safe: true
auto_approve_low: false
# Onay Timeout Süreleri
approval_timeout_high: 5 minutes
approval_timeout_critical: 2 minutes
Roadmap'te yer alan AI geliştirmeleri:
This project is licensed under the MIT License - see the LICENSE file for details.
Built with ❤️ by the Kairos AI Team
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