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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.
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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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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| 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― Faz 0: Stabilizasyon TamamlandΔ±! Tek komutla tΓΌm sistemi baΕlatabilirsiniz.
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:
| 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/
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
# 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 yΓΆnetimi sunar. AI, sistem saΔlΔ±ΔΔ±nΔ± sΓΌrekli izler ve sorunlarΔ± otomatik olarak tespit ederek Γ§ΓΆzΓΌm ΓΆnerileri sunar.
AI sistemi Εu bileΕenleri sΓΌrekli izler:
AI, Εu pattern'leri otomatik olarak tespit eder:
Tespit edilen sorunlar iΓ§in AI Εu eylemleri ΓΆnerebilir: