mcp-ecosystem-platform
π Ultimate Developer Productivity Suite - 11 specialized MCP servers for AI-powered code analysis, security scanning, browser automation, and workflow orchestration. FastAPI + React + TypeScript + Docker ready.
Install / Use
claude mcp add turtir-ai -- npx -y github:turtir-ai/mcp-ecosystem-platformIf the server publishes to npm under a different name, use that package instead β check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
SecuritySupported Platforms
Skill content
View source on GitHubπ MCP Ecosystem Platform
<div align="center">
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.
</div>π Key Features
π€ 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
π 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
π 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
π 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
ποΈ Architecture
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β Frontend (React + TS) β
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β FastAPI Backend β
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β MCP Server Layer β
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β PostgreSQL β Redis β Docker β Kubernetes β
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π§ 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 |
π Quick Start
π― Faz 0: Stabilizasyon TamamlandΔ±! Tek komutla tΓΌm sistemi baΕlatabilirsiniz.
Prerequisites
- Python 3.11+
- Node.js 18+ (Frontend iΓ§in)
- Git
β‘ 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! π The script will:
- β Check prerequisites
- π¦ Install dependencies automatically
- π Start all services in the correct order
- π§ Fix VS Code extension connection issues
π 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
π§ Port Standardization
| Service | Port | URL | |---------|------|-----| | Frontend | 3000 | http://localhost:3000 | | Backend API | 8001 | http://localhost:8001 | | MCP Manager | 8009 | http://localhost:8009 |
π οΈ 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>
π Project Structure
mcp-ecosystem-platform/
βββ π backend/ # FastAPI backend
β βββ π app/
β β βββ π core/ # Core interfaces and config
β β βββ π services/ # Business logic services
β β βββ π api/ # API routes
β β βββ π models/ # Database models
β β βββ π main.py # FastAPI application
β βββ π tests/ # Backend tests
β βββ π requirements.txt # Python dependencies
β βββ π Dockerfile # Backend container
βββ π frontend/ # React frontend
β βββ π src/
β β βββ π components/ # React components
β β βββ π pages/ # Page components
β β βββ π services/ # API clients
β β βββ π types/ # TypeScript types
β βββ π package.json # Node dependencies
β βββ π Dockerfile.dev # Frontend container
βββ π mcp-servers/ # MCP server configurations
βββ π vscode-extension/ # VS Code extension
βββ π docker-compose.yml # Development environment
βββ π .env.example # Environment template
βββ π README.md # This file
π§ 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.
π§ͺ 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
π 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/
π Monitoring & Analytics
- Health Checks:
/healthendpoint for all services - Metrics: Prometheus metrics at
/metrics - Logs: Structured logging with correlation IDs
- Tracing: Distributed tracing support
π€ Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - 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
π€ AI ile Sistem YΓΆnetimi
MCP Ecosystem Platform, AI destekli proaktif sistem yΓΆnetimi sunar. AI, sistem saΔlΔ±ΔΔ±nΔ± sΓΌrekli izler ve sorunlarΔ± otomatik olarak tespit ederek Γ§ΓΆzΓΌm ΓΆnerileri sunar.
π AkΔ±llΔ± Sistem Δ°zleme
AI sistemi Εu bileΕenleri sΓΌrekli izler:
- MCP SunucularΔ±: TΓΌm 11 MCP sunucusunun durumu ve performansΔ±
- Sistem KaynaklarΔ±: CPU, bellek, disk kullanΔ±mΔ±
- VeritabanΔ± PerformansΔ±: Sorgu sΓΌreleri ve baΔlantΔ± havuzu durumu
- AΔ BaΔlantΔ±larΔ±: API yanΔ±t sΓΌreleri ve baΔlantΔ± durumu
π¨ Proaktif Hata Tespiti
AI, Εu pattern'leri otomatik olarak tespit eder:
- Tekrarlayan Hatalar: Belirli aralΔ±klarla tekrarlanan sistem hatalarΔ±
- Performans DΓΌΕΓΌΕΓΌ: Zaman iΓ§inde artan yanΔ±t sΓΌreleri
- Kaynak TΓΌkenmesi: Kritik eΕiklere yaklaΕan sistem kaynaklarΔ±
- Cascade Hatalar: Birden fazla bileΕeni etkileyen zincirleme hatalar
π οΈ AI Eylem Γnerileri
Tespit edilen sorunlar iΓ§in AI Εu eylemleri ΓΆnerebilir:
π’ Otomatik OnaylΔ± (DΓΌΕΓΌk Risk)
- Sistem durumu sorgulama
- Log dosyalarΔ±nΔ± okuma
- Performans metriklerini toplama
- SΓΌreΓ§ analizi yapma
π‘ KullanΔ±cΔ± OnayΔ± Gerekli (Orta Risk)
- Dosya dΓΌzenleme iΕlemleri
- KonfigΓΌrasyon deΔiΕiklikleri
- Otomatik dΓΌzeltme uygulama
- Git iΕlemleri
π΄ YΓΌksek Riskli (AΓ§Δ±k Onay Gerekli)
- MCP sunucu yeniden
Truncated for display β read the full file on GitHub.
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