mcp-games

# MCP Games A game development framework that integrates the Model Context Protocol (MCP) for AI-powered gaming experiences. ## Features ### Core Game Engine - Complete game object system with components - Physics system with collision detection - Rendering system with sprites and particles - Input handling system - Sound system for audio playback - Scene management - Event system ### AI Integration - Advanced AI controller with MCP integration - Memory system for NPCs to remember events and interactions - Emotion system for realistic NPC behaviors - Behavior system with state machines - Dialog generation using AI models - Decision making based on context and memories ### MCP Features - AI-powered NPCs and game mechanics - Procedural content generation - Interactive storytelling - Real-time decision making - Memory and context-aware interactions ## Installation ```bash # Clone the repository git clone https://github.com/ahmed202020803/mcp-games.git cd mcp-games # Install dependencies pip install -r requirements.txt ``` ## Usage ### Basic Example ```python from mcp_games.engine import GameEngine from mcp_games.ai import AIController # Initialize game engine engine = GameEngine() # Create AI controller ai = AIController(engine) # Register game objects player = engine.create_player() npc = engine.create_npc("villager") # Set up AI behavior ai.set_behavior(npc, "friendly_villager") # Start game loop engine.start() ``` ### Advanced Example ```python from mcp_games.engine import AdvancedGameEngine from mcp_games.ai import AdvancedAIController from mcp_games.physics import Vector3 # Initialize advanced game engine engine = AdvancedGameEngine(screen_width=1024, screen_height=768) # Initialize advanced AI controller with MCP API key ai = AdvancedAIController(engine, mcp_api_key="your-api-key") # Create player with physics and rendering player = engine.create_player() engine.add_collider(player, "sphere", radius=0.5) engine.add_render_component(player, "sprites/player.png") # Create NPC with advanced AI npc = engine.create_npc("villager") engine.add_collider(npc, "sphere", radius=0.5) engine.add_render_component(npc, "sprites/villager.png") # Add memories to NPC ai.add_memory( npc.id, "I am a villager living in this area.", importance=0.8, category="identity" ) # Set emotions for NPC ai.update_emotion(npc.id, "happiness", 0.7) # Create particle effects particles = engine.create_particle_system(Vector3(0, 1, 0)) particles.start() # Start game loop engine.start() ``` ## Examples The repository includes two example games: 1. **Simple Game** (`examples/simple_game.py`): A basic example showing core functionality 2. **Advanced Game** (`examples/advanced_game.py`): A comprehensive example demonstrating all features To run the advanced example: ```bash python examples/advanced_game.py ``` Controls: - WASD: Move player - ESC: Quit - P: Pause/Resume - F1: Toggle debug info ## Project Structure ``` mcp-games/ ├── assets/ # Game assets │ ├── sprites/ # Image files │ └── sounds/ # Audio files ├── config/ # Configuration files ├── src/ # Source code │ ├── engine/ # Game engine core │ │ ├── physics.py # Physics system │ │ └── renderer.py # Rendering system │ ├── ai/ # AI integration components │ │ ├── behavior.py # Behavior system │ │ └── advanced_ai.py # Advanced AI with MCP │ └── utils/ # Utility functions ├── examples/ # Example games and demos ├── docs/ # Documentation ├── tests/ # Test suite ├── requirements.txt # Dependencies └── README.md # Documentation ``` ## MCP Integration The framework integrates with the Model Context Protocol (MCP) to provide AI-powered gaming experiences: - **Dialog Generation**: NPCs can generate contextually relevant dialog based on their memories, emotions, and current situation - **Decision Making**: AI can make decisions for NPCs based on their personality, memories, and context - **Memory System**: NPCs remember interactions and events, which influence their future behavior - **Emotion System**: NPCs have emotional states that evolve over time and affect their behavior ## Contributing 1. Fork the repository 2. Create a feature branch 3. Commit your changes 4. Push to the branch 5. Create a Pull Request ## License This project is licensed under the MIT License - see the LICENSE file for details.