A comprehensive AI agent system built with reinforcement learning, multi-agent coordination, and cloud integration capabilities. This project provides a modern, scalable platform for building intelligent agents that can learn, adapt, and collaborate to solve complex tasks.
- Multi-Agent System: Coordinate multiple specialized agents for complex tasks
- Reinforcement Learning: Advanced RL algorithms including DQN, PPO, and meta-learning
- Cloud Integration: Deploy and scale across AWS, Azure, and Google Cloud Platform
- Real-time Communication: WebSocket support for live agent interactions
- Memory Systems: Persistent and distributed memory with semantic search
- Tool Integration: Extensible tool system with performance tracking
- Brand Agent Platform: AI-powered conversational agents for marketing
- Trading System: Algorithmic trading with TradingView integration
- Document Processing: Advanced NLP pipeline with vector stores
- Semantic Agents: Context-aware agents with knowledge graphs
- Infinite Loop System: Continuous improvement and content generation
- Python 3.9+
- Redis (optional, for distributed features)
- Node.js 18+ (for web UI)
# Clone the repository
git clone https://github.com/your-org/DataMCPServerAgent.git
cd DataMCPServerAgent
# Install Python dependencies
pip install -r requirements.txt
# Install UI dependencies
cd agent-ui
npm install
cd ..
# Copy environment template
cp .env.example .env
# Edit .env with your configuration
# Start the API server
python app/main_consolidated.py api
# Start the web interface
cd agent-ui && npm run dev
# Access the application
# API: http://localhost:8003
# UI: http://localhost:3000
DataMCPServerAgent follows Clean Architecture principles with Domain-Driven Design:
# Start API server
python app/main_simple_consolidated.py api
# Or start CLI interface
python app/main_simple_consolidated.py cli
# Start server with hot reload
python app/main_simple_consolidated.py api --reload
# Check system status
curl http://localhost:8003/health
# View API documentation
# Open http://localhost:8003/docs in your browser
# Interactive CLI
python app/main_simple_consolidated.py cli
# Available commands:
# - help: Show available commands
# - status: Show system status
# - agents: List available agents
# - tasks: Manage tasks
# - structure: Show system architecture
# Basic RL mode
RL_MODE=basic python src/core/reinforcement_learning_main.py
# Advanced RL with modern algorithms
RL_MODE=modern_deep RL_ALGORITHM=ppo python src/core/reinforcement_learning_main.py
# Multi-agent learning
RL_MODE=multi_agent python src/core/reinforcement_learning_main.py