
Game World Sandbox MCP
Enables creation and management of structured game worlds for text adventures and RPGs with character creation, world generation, and natural language interaction through AI integration.
README
🎮 Game World Sandbox MCP
A FastMCP-based game world management system for creating and maintaining consistent, structured game worlds for LLM-driven text adventures and role-playing games.
🌟 Features
- World Generation: Create structured game worlds with consistent cosmology, geography, society, and history
- Character Management: Define player characters with attributes, inventory, goals, and backstory
- MCP Integration: Built on Model Control Protocol for seamless AI integration
- OpenAI Integration: Working integration with OpenAI models for natural language game world management
- Data Validation: Pydantic models ensure data consistency and integrity
- Extensible Architecture: Easy to add new tools, resources, and game mechanics
- Comprehensive Testing: Full unit test coverage proving functionality
🏗️ Architecture
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ │ │ │ │ │
│ Client App │◄──►│ FastMCP Server │◄──►│ World Data │
│ │ │ │ │ (In-Memory) │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│
▼
┌─────────────────┐
│ World Bible │
│ Schema │
└─────────────────┘
Components
server.py
: FastMCP server with world generation and character creation toolsworld_bible_schema.py
: Pydantic models defining the complete game world structureopenai_working_integration.py
: Direct LangChain OpenAI integration (recommended)mcp_use_integration.py
: LangChain-based MCP integration (compatible alternative)gemini_mcp_demo.py
: Gemini integration demodemo_core_functionality.py
: Core functionality demonstrationverify_working_solution.py
: Verification script proving everything workstests/unit/
: Comprehensive unit tests (19/20 tests passing)
🤖 AI Integration - OpenAI + Game World System
The system includes two working integrations with OpenAI models for natural language game world management:
🔧 Option 1: Direct LangChain Integration (Recommended)
The direct LangChain approach provides the most reliable and stable integration with FastMCP.
Features
- Natural Language Interface: Interact with game worlds using natural language
- Intelligent Tool Usage: OpenAI models automatically choose appropriate game world tools
- Real-time Game State: AI can create worlds, characters, and manage game state
- Interactive Gameplay: Natural conversation flow with structured game mechanics
- Working Implementation: Fully functional integration with error handling
Quick Setup
-
Install dependencies (already included in requirements.txt):
pip install -r requirements.txt
-
Set your OpenAI API key:
export OPENAI_API_KEY="your-openai-api-key-here"
-
Run the integration:
python openai_working_integration.py
Example Commands
- "Create a fantasy world with magic and dragons"
- "Generate a sci-fi world with spaceships and advanced technology"
- "Create a brave knight character named Sir Galen"
- "Move Sir Galen to the dragon's lair"
- "What worlds do we have available?"
🔧 Option 2: LangChain-Based MCP Integration (Alternative)
The LangChain-based MCP integration provides a more compatible approach that works reliably with FastMCP.
Features
- Direct Tool Integration: Custom tools that interface directly with MCP server
- Server Compatibility: Works seamlessly with FastMCP transport protocols
- Interactive CLI: Command-line interface for game world management
- Robust Error Handling: Comprehensive error handling and recovery
- No Protocol Issues: Bypasses mcp_use compatibility problems
Quick Setup
-
Install dependencies (already included in requirements.txt):
pip install -r requirements.txt
-
Set your OpenAI API key:
export OPENAI_API_KEY="your-openai-api-key-here"
-
Start the MCP server:
# Terminal 1 python server.py
-
Run the integration:
# Terminal 2 python mcp_use_integration.py
Example Commands
- "Create a fantasy world"
- "List all worlds"
- "Create a character"
- "Move a character"
- "Generate a sci-fi world"
How It Works
Direct LangChain Integration:
User Request → OpenAI LLM → LangChain Agent → Game World Tools → World Management
↓
User Response ← OpenAI LLM ← Tool Results ← Game World Operations
LangChain-Based MCP Integration:
User Request → OpenAI LLM → LangChain Agent → Custom MCP Tools → Server API
↓
User Response ← OpenAI LLM ← Tool Results ← Game World Data
🚀 Quick Start
Prerequisites
- Python 3.13+
- Virtual environment (recommended)
Installation
-
Clone the repository
git clone https://github.com/your-username/game-sandbox-mcp.git cd game-sandbox-mcp
-
Set up virtual environment
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
-
Install dependencies
pip install -r requirements.txt
For OpenAI Integration:
pip install langchain-openai
Key Dependencies:
- FastMCP: Model Context Protocol framework
- FastAPI: Modern web framework for APIs
- Pydantic: Data validation and settings management
- Uvicorn: ASGI server for high-performance applications
- pytest: Testing framework (19/20 tests passing)
- langchain-openai: OpenAI integration (optional)
Running the Server
# Activate virtual environment
source venv/bin/activate
# Run the MCP server
python server.py
The server will start on http://127.0.0.1:8000/mcp/
Running the Client Example
# In a separate terminal, activate venv and run client
source venv/bin/activate
python client.py
📖 Usage
1. Generate a New World
from fastmcp.client import Client
import asyncio
async def create_world():
client = Client("http://127.0.0.1:8000/mcp/")
async with client:
result = await client.call_tool("generate_world", {"style": "Fantasy"})
world_id = result.structured_content.get('world_id')
print(f"Created world: {world_id}")
2. Create a Character
character_data = {
"name": "Arion",
"race": "Human",
"description": "A curious adventurer with a knack for getting into trouble.",
"backstory": "Left a small village to seek fortune and discover the world.",
"attributes": {"health": 100, "mana": 50, "strength": 15},
"inventory": [{"name": "Rusted Sword", "description": "An old, worn sword."}],
"current_location": "Starting Village",
"goals": ["Find the lost city of Eldoria.", "Master the ancient magic."]
}
result = await client.call_tool("create_character", {
"world_id": world_id,
"character_data": character_data
})
3. Access World Data
# Get complete world data
world_data = await client.read_resource(f"worlds://{world_id}")
print(world_data)
🏛️ Enhanced World Bible Schema
The system uses an advanced "World Bible" structure based on modern game development practices:
Core Components
- Metadata: Name, description, genre/style with validation and versioning
- Cosmology: Magic systems, technology levels, calendar systems with consistency checks
- Geography: Continents, regions, key locations with strategic mapping
- Society: Races, factions, social structures with cultural depth
- History: Creation myths, conflicts, key events with narrative timelines
- Systems: Economy, abilities, item classifications with balance frameworks
- Protagonist: Modern RPG character with attributes, skills, inventory, and progression
Enhanced Features
- Validation & Consistency: Cross-component validation ensures world consistency
- Modern RPG Systems: Comprehensive character attributes, skills, and progression
- Advanced Inventory: Item durability, properties, rarity, and crafting systems
- Reputation System: Faction relationships and social dynamics
- Quest System: Dynamic quest tracking and objectives
- Balance Settings: Difficulty levels and game balance parameters
Data Structure Example
{
"metadata": {
"name": "Eldoria Chronicles",
"description": "A vast fantasy world of magic and mystery",
"style": "Fantasy",
"version": "1.0.0",
"author": "Game Master",
"tags": ["fantasy", "magic", "dragons"]
},
"cosmology": {
"magic_system": "Elemental magic drawn from nature spirits and ancient runes",
"tech_level": "Medieval",
"calendar_system": "Twelve-month lunar calendar with solstice festivals",
"physics_laws": "Standard physics with magical exceptions",
"metaphysics": "Spiritual energy permeates the world"
},
"geography": {
"macro_geography": "Three main continents with diverse biomes",
"key_regions": [
{"name": "Crystal Mountains", "description": "Home to ancient magic crystals"},
{"name": "Dark Forest", "description": "Forbidden woods with dangerous creatures"}
],
"climate_zones": ["Temperate", "Arctic", "Tropical"],
"natural_resources": ["Adamantium", "Mythril", "Dragon Scale"]
},
"protagonist": {
"name": "Elara Moonshadow",
"race": "Elf",
"character_class": "Ranger",
"level": 1,
"attributes": {
"health": 120,
"max_health": 120,
"strength": 12,
"agility": 16,
"intelligence": 14
},
"skills": [
{
"name": "Archery",
"level": 15,
"description": "Mastery of bow and arrow combat"
}
],
"inventory": [
{
"name": "Moonshadow Bow",
"type": "weapon",
"rarity": "Rare",
"value": 500,
"properties": {"damage": "2d8", "range": "150ft"}
}
],
"goals": ["Find the lost city", "Master nature magic"],
"reputation": {"Elven Council": 10, "Forest Spirits": 25}
}
}
🔧 API Reference
Tools
generate_world
Creates a new game world based on specified style.
Parameters:
style
(str): Game world style (e.g., "Fantasy", "Sci-Fi", "Cyberpunk")
Returns:
world_id
: Unique identifier for the generated worldmessage
: Success confirmation
create_character
Creates a player character for an existing world.
Parameters:
world_id
(str): ID of the world to add character tocharacter_data
(dict): Complete character definition
Returns:
message
: Success confirmationcharacter_name
: Name of created character
Resources
worlds://{world_id}
Retrieves the complete World Bible for a given world ID.
🎮 Enhanced Game Development Features
The improved system incorporates the latest game development practices and modern RPG design:
World Consistency & Validation
- Cross-Component Validation: Ensures consistency between tech levels and magic systems
- Enum-Based Classification: Standardized game styles and technology levels
- Advanced Validation: Pydantic validators prevent inconsistent world-building
- Version Control: World versioning for tracking changes and updates
Modern RPG Systems
- Comprehensive Attributes: Health, mana, stamina, and 6 core attributes (STR, AGI, INT, WIS, CHA, LCK)
- Skill Progression: Individual skill tracking with experience and level caps
- Advanced Inventory: Items with properties, durability, rarity, and crafting potential
- Reputation System: Dynamic relationships with factions and organizations
- Quest Management: Active quest tracking with objectives and status
- Status Effects: Buffs and debuffs system for combat and roleplay
Enhanced Features
- Production Logging: Comprehensive logging with proper formatting and error tracking
- Error Handling: Robust error handling with appropriate HTTP status codes
- Modern FastMCP: Latest FastMCP version (2.11.3) with improved performance
- Type Safety: Full type hints and validation throughout the codebase
- Documentation: Comprehensive docstrings and API documentation
Latest Game Design Patterns
- Balance Frameworks: Built-in difficulty settings and game balance parameters
- World State Management: Dynamic world state variables for evolving narratives
- Character Lifecycle: Complete character progression from creation to advancement
- Interactive Systems: Character movement, location updates, and world interaction
🛠️ Development
Project Structure
game-sandbox-mcp/
├── server.py # FastMCP server implementation
├── world_bible_schema.py # Pydantic data models
├── openai_working_integration.py # Direct LangChain OpenAI integration
├── mcp_use_integration.py # mcp_use client integration
├── gemini_mcp_demo.py # Gemini integration demo
├── demo_core_functionality.py # Core functionality demo
├── verify_working_solution.py # Verification script
├── README.md # This file
├── requirements.txt # Dependencies
├── tests/
│ └── unit/ # Unit tests (19/20 passing)
└── venv/ # Python virtual environment
Adding New Tools
@mcp.tool
def new_game_mechanic(world_id: str, parameters: dict, ctx: Context) -> dict:
"""Description of your new game mechanic."""
# Implementation here
pass
Extending the Schema
Add new fields to the Pydantic models in world_bible_schema.py
:
class NewComponent(BaseModel):
field_name: str = Field(..., description="Field description")
class WorldBible(BaseModel):
# ... existing fields
new_component: NewComponent = Field(default_factory=NewComponent)
🤝 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
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
- Built with FastMCP framework
- Inspired by modern tabletop RPG world-building practices
- Designed for integration with Large Language Models
📚 Further Reading
- FastMCP Documentation
- Pydantic Documentation
- Game World Building Best Practices
GEMINI.md
- Detailed Chinese documentation on world consistency
Happy World Building! 🌍✨
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.