"""
MCP Client for Agent2Robot
Handles communication with MCP servers for vehicle design
"""

import json
from typing import Dict, List, Any

class MCPClient:
    """Client for interacting with MCP servers for vehicle design tasks"""
    
    def __init__(self):
        self.connected = False
        self.server_capabilities = {}
        # Auto-connect on initialization for demo
        self.connect()
    
    def connect(self, server_url: str = None) -> bool:
        """Connect to MCP server"""
        # Simulate connection for demo purposes
        self.connected = True
        self.server_capabilities = {
            "design_optimization": True,
            "performance_analysis": True,
            "specification_generation": True,
            "validation": True,
            "simulation_generation": True
        }
        return True
    
    def generate_design(self, vehicle_type: str, requirements: str) -> Dict[str, Any]:
        """Generate vehicle design using MCP server"""
        if not self.connected:
            self.connect()
        
        # Simulate MCP server response
        design_data = {
            "vehicle_type": vehicle_type,
            "requirements": requirements,
            "optimization_score": 95,
            "generated_features": [
                "Advanced navigation system",
                "Obstacle avoidance capabilities",
                "Energy-efficient design",
                "Modular architecture",
                "Real-time sensor fusion",
                "Adaptive control systems"
            ],
            "performance_metrics": {
                "speed": "Optimized for task requirements",
                "efficiency": "95% energy efficiency", 
                "reliability": "High reliability rating",
                "maintainability": "Excellent serviceability"
            },
            "technical_specs": {
                "power_system": "Advanced battery management",
                "sensors": "LiDAR, cameras, IMU, GPS",
                "communication": "5G, WiFi, Bluetooth",
                "processing": "Edge AI computing unit"
            },
            "simulation_ready": True
        }
        
        return design_data
    
    def generate_simulation_video(self, design_specs: Dict[str, Any]) -> str:
        """Generate simulation video URL using MCP server"""
        # Simulate video generation - in real implementation this would
        # communicate with MCP server to generate actual simulation
        vehicle_type = design_specs.get("vehicle_type", "robot").lower()
        
        # Return a placeholder video URL or description
        simulation_info = f"""
🎬 Simulation Video Generated via MCP Server

Vehicle Type: {design_specs.get('vehicle_type', 'Unknown')}
Simulation Status: ✅ Generated Successfully
Duration: 30 seconds
Resolution: 1080p HD

📊 Simulation Features:
• Physics-based movement simulation
• Environmental interaction modeling  
• Performance metrics visualization
• Real-time sensor data overlay

🎯 Video Content:
• Vehicle navigation demonstration
• Obstacle avoidance scenarios
• Performance optimization display
• MCP-validated design execution

Note: Full video simulation requires MCP server connection.
For hackathon demo, this represents MCP-generated simulation data.
"""
        return simulation_info
    
    def validate_design(self, design_specs: Dict[str, Any]) -> Dict[str, Any]:
        """Validate design specifications using MCP server"""
        return {
            "valid": True,
            "confidence": 0.95,
            "validation_notes": "Design meets all requirements and constraints"
        }
    
    def get_server_info(self) -> Dict[str, Any]:
        """Get MCP server information"""
        return {
            "name": "Agent2Robot MCP Server",
            "version": "1.0.0",
            "capabilities": self.server_capabilities,
            "status": "connected" if self.connected else "disconnected"
        }