🚀 MCP Ecosystem Platform

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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.

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🌟 Key Features

🤖 AI-Powered Development

• Smart Git Review: AI-driven code analysis and review automation
• Intelligent Workflow Orchestration: Chain MCP servers for complex tasks
• Multi-Model AI Access: Groq Llama 3.1, OpenRouter, and more
• Real-time Code Intelligence: Context-aware suggestions and analysis

🔒 Security & Monitoring

• API Key Protection: Advanced sniffer and protection mechanisms
• Network Analysis: Real-time traffic monitoring and optimization
• Security Scanning: Continuous threat detection and vulnerability assessment
• Automated Compliance: Security best practices enforcement

🌐 Web & Browser Automation

• Real Browser Control: No-simulation browser automation
• Deep Web Research: Comprehensive competitive intelligence
• Data Extraction: Automated web scraping and analysis
• Cross-platform Testing: Multi-browser compatibility testing

📊 Developer Dashboard

• Unified Control Interface: Single pane of glass for all operations
• Real-time Metrics: Performance monitoring and analytics
• Workflow Visualization: Interactive workflow designer
• Team Collaboration: Shared workspaces and project management

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Frontend (React + TS)                    │
├─────────────────────────────────────────────────────────────┤
│                   FastAPI Backend                          │
├─────────────────────────────────────────────────────────────┤
│                  MCP Server Layer                          │
├─────────────────────────────────────────────────────────────┤
│  PostgreSQL  │    Redis     │   Docker    │  Kubernetes   │
└─────────────────────────────────────────────────────────────┘

🔧 MCP Servers (11 Specialized Servers)

| 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 |

🚀 Quick Start

🎯 Faz 0: Stabilizasyon Tamamlandı! Tek komutla tüm sistemi başlatabilirsiniz.

Prerequisites

• Python 3.11+
• Node.js 18+ (Frontend için)
• Git

⚡ One-Command Startup (Recommended)

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:

• ✅ Check prerequisites
• 📦 Install dependencies automatically
• 🚀 Start all services in the correct order
• 🔧 Fix VS Code extension connection issues

🌐 Access the Platform

• Frontend: http://localhost:3000
• Backend API: http://localhost:8001
• API Documentation: http://localhost:8001/docs
• Health Check: http://localhost:8001/health
• MCP Status: http://localhost:8001/api/v1/mcp/status
• MCP Manager: http://localhost:8009

🔧 Port Standardization

| Service | Port | URL | |---------|------|-----| | Frontend | 3000 | http://localhost:3000 | | Backend API | 8001 | http://localhost:8001 | | MCP Manager | 8009 | http://localhost:8009 |

🛠️ Manual Setup (Advanced)

<details> <summary>Click to expand manual setup instructions</summary>

1. Clone & Setup

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

2. Backend Setup

cd backend
python -m venv venv

# Windows
venv\Scripts\activate
# Linux/Mac
source venv/bin/activate

pip install -r requirements.txt

3. Frontend Setup

cd frontend
npm install

4. Start Services Manually

# 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

</details>

📁 Project Structure

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

🔧 Configuration

Environment Variables

# 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

MCP Server Configuration

The platform automatically discovers and configures MCP servers from your .kiro/settings/mcp.json file.

🧪 Testing

Backend Tests

cd backend
pytest tests/ -v --cov=app

Frontend Tests

cd frontend
npm test

Integration Tests

# Run full test suite
docker-compose -f docker-compose.test.yml up --build

🚀 Deployment

Docker Production

# Build and start production containers
docker-compose -f docker-compose.prod.yml up -d

Kubernetes

# Deploy to Kubernetes
kubectl apply -f k8s/

📊 Monitoring & Analytics

• Health Checks: /health endpoint for all services
• Metrics: Prometheus metrics at /metrics
• Logs: Structured logging with correlation IDs
• Tracing: Distributed tracing support

🤝 Contributing

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

Development Guidelines

• Follow PEP 8 for Python code
• Use TypeScript for all frontend code
• Write comprehensive tests
• Update documentation
• Follow conventional commits

🤖 AI ile Sistem Yönetimi

MCP Ecosystem Platform, AI destekli proaktif sistem yönetimi sunar. AI, sistem sağlığını sürekli izler ve sorunları otomatik olarak tespit ederek çözüm önerileri sunar.

🔍 Akıllı Sistem İzleme

AI sistemi şu bileşenleri sürekli izler:

• MCP Sunucuları: Tüm 11 MCP sunucusunun durumu ve performansı
• Sistem Kaynakları: CPU, bellek, disk kullanımı
• Veritabanı Performansı: Sorgu süreleri ve bağlantı havuzu durumu
• Ağ Bağlantıları: API yanıt süreleri ve bağlantı durumu

🚨 Proaktif Hata Tespiti

AI, şu pattern'leri otomatik olarak tespit eder:

• Tekrarlayan Hatalar: Belirli aralıklarla tekrarlanan sistem hataları
• Performans Düşüşü: Zaman içinde artan yanıt süreleri
• Kaynak Tükenmesi: Kritik eşiklere yaklaşan sistem kaynakları
• Cascade Hatalar: Birden fazla bileşeni etkileyen zincirleme hatalar

🛠️ AI Eylem Önerileri

Tespit edilen sorunlar için AI şu eylemleri önerebilir:

🟢 Otomatik Onaylı (Düşük Risk)

• Sistem durumu sorgulama
• Log dosyalarını okuma
• Performans metriklerini toplama
• Süreç analizi yapma

🟡 Kullanıcı Onayı Gerekli (Orta Risk)

• Dosya düzenleme işlemleri
• Konfigürasyon değişiklikleri
• Otomatik düzeltme uygulama
• Git işlemleri

🔴 Yüksek Riskli (Açık Onay Gerekli)

• MCP sunucu yeniden