MCPy is a next-generation, ultra-optimized Minecraft server engine powered by Python, Cython, and advanced scientific computing libraries. Our mission is to deliver exceptional performance and flexibility, making Minecraft server development both accessible and future-proof.
Note:
MCPy is under active development and is not yet feature-complete. The codebase contains known errors and is unstable. We welcome your bug reports and contributions to help us reach our goals faster!
🚧 Project Status
- The project is incomplete and contains known issues.
- Major features are under active development; the codebase is unstable.
- We highly value contributions and bug reports from the community.
🚀 Features at a Glance
- Cython-Accelerated Core: Event-driven server engine approaching C-level performance.
- Scientific Computing Backbone: Integrates NumPy, SciPy, and Polars for high-efficiency operations.
- Zero-Overhead Networking: Asynchronous, non-blocking, protocol-optimized networking.
- Sophisticated Entity System: Efficient, extensible entity management with advanced AI support.
- Robust Persistence Layer: Powered by PostgreSQL and SQLAlchemy ORM for reliable data storage.
- Comprehensive Benchmarking: Built-in performance analytics and profiling tools.
- Extensible Plugin Framework: Easily add server modifications.
- Real-Time Monitoring: Prometheus & Grafana integration for live metrics.
📐 Architecture Overview
MCPy is modular, with five high-performance core components:
server_core.pyx- Event-driven request handling
- Adaptive, high-precision tick system
- Dynamic worker thread pool management
- Real-time performance profiling
world_engine.pyx- Procedural terrain generation with multi-octave noise and advanced biomes
- Multi-threaded chunk generation & memory-efficient terrain storage
network_core.pyx- Zero-copy packet serialization and protocol-level compression
- Robust connection pooling & DDoS mitigation
entity_system.pyx- Spatial hash-based entity tracking and multi-threaded physics
- Modular AI behavior trees
persistence- SQLAlchemy ORM for PostgreSQL/SQLite
- Efficient chunk serialization and transactional world state
| Metric | Target Value |
|---|
| Scalability | 20 TPS with 100+ concurrent players |
| Memory Usage | <2 GB for 10,000 chunks |
| Latency | <50 ms per player action |
| Reliability | 100% test coverage for core modules |
| Throughput | 10,000+ entity updates per tick |
⚙️ Technical Highlights
- Static typing (
cdef) and aggressive compiler directives - Direct NumPy buffer access and pointer arithmetic
- Multi-threaded parallelism via thread pools
Entity System
- Hierarchical, component-based design
- O(1) spatial partitioning via custom memory pools
- Adaptive Level-of-Detail (LOD) entity management
World Generation
- Multi-octave Perlin/Simplex noise
- Voronoi-based biome transitions
- Erosion, cave, and structure algorithms
- 10x chunk compression for storage efficiency
📦 Installation
Prerequisites
- Python 3.9+ (3.11+ recommended)
- Modern C++ compiler (VS 2019+ / GCC 9+)
- PostgreSQL 13+ (for production)
- Minimum 8 GB RAM (16 GB recommended)
Quick Setup
git clone https://github.com/magi8101/mcpy.git
cd mcpy
# Windows
setup.bat
# Linux/macOS
chmod +x setup.sh
./setup.sh
Manual Installation
git clone https://github.com/magi8101/mcpy.git
cd mcpy
python -m venv .venv
# Windows:
.venv\Scripts\activate
# Linux/macOS:
source .venv/bin/activate
pip install -r _requirements.txt
pip install -e ".[dev]"
pip install -e ".[ai]" # Optional: Enable AI features
python check_dependencies.py
python setup.py build_ext --inplace
🚀 Running the Server
# Using setup scripts
# Windows:
setup.bat run
# Linux/macOS:
./setup.sh run
# Directly from the command line
python -m mcpy.server
python -m mcpy.server --config custom_config.toml --world my_world
python -m mcpy.server --performance-mode --max-players 100
python -m mcpy.server --debug --log-level debug
Command Line Options
| Option | Description |
|---|
--config PATH | Path to TOML config file |
--world PATH | World directory |
--port NUMBER | Network port (default: 25565) |
--max-players NUMBER | Max players (default: 20) |
--view-distance NUMBER | Chunk view distance (default: 10) |
--performance-mode | Extra performance optimizations |
--debug | Enable debug mode |
--log-level LEVEL | Set log level (default: info) |
--backup | Enable automatic backups |
🗄️ Database Configuration
SQLite (Default)
[database]
type = "sqlite"
path = "world/mcpy.db"
journal_mode = "WAL"
synchronous = "NORMAL"
PostgreSQL (Production)
[database]
type = "postgresql"
host = "localhost"
port = 5432
dbname = "mcpy"
user = "postgres"
password = "your_password"
pool_size = 10
max_overflow = 20
echo = false
💾 Persistence Features
- Transactional World Saving
with session.begin():
for chunk in dirty_chunks:
session.add(ChunkModel.from_chunk(chunk))
- Efficient Chunk Serialization
chunk_data = np.savez_compressed(io_buffer,
blocks=chunk.blocks,
heightmap=chunk.heightmap,
biomes=chunk.biomes)
- Player Data Management
player_model = PlayerModel(
uuid=player.uuid,
username=player.username,
position=json.dumps([player.x, player.y, player.z]),
inventory=pickle.dumps(player.inventory, protocol=5),
stats=json.dumps(player.stats)
)
- Intelligent Auto-saving: Only modified chunks/entities are saved
- Automated Backups: Configurable intervals & retention
🧪 Development & Testing
pytest # Run full test suite
pytest tests/test_entity_system.py # Entity system tests
python -m benchmarks.benchmark # Benchmarks
python -m mcpy.profiling.profile_module world_engine # Profile module
pytest --cov=mcpy --cov-report=html # Test coverage report
- Entity System
entity_spatial_hash = {(int(e.x/16), int(e.z/16)): [] for e in entities}
for entity in entities:
entity_spatial_hash[(int(entity.x/16), int(entity.z/16))].append(entity)
- World Engine
with ThreadPoolExecutor(max_workers=os.cpu_count()) as executor:
futures = [executor.submit(generate_chunk, x, z) for x, z in chunk_coords]
chunks = [f.result() for f in futures]
- Network Optimization
cdef char* buffer = <char*>malloc(packet_size)
memcpy(buffer, &packet_header, sizeof(packet_header))
memcpy(buffer + sizeof(packet_header), packet_data, packet_data_size)
🔧 Advanced Features
Plugin System
Add custom commands and behaviors easily:
from mcpy.plugins import Plugin, event
class TeleportPlugin(Plugin):
@event("player.command")
def on_command(self, player, command, args):
if command == "tp" and len(args) >= 1:
target = self.server.get_player_by_name(args[0])
if target:
player.teleport(target.x, target.y, target.z)
return True
return False
Real-time Monitoring
Integrated Prometheus/Grafana support:
[monitoring]
enabled = true
prometheus_port = 9090
metrics = ["tps", "memory_usage", "players_online", "chunks_loaded"]
AI Entity Behaviors
Flexible, behavior-tree-driven AI:
class ZombieAI(MobAI):
def setup_behaviors(self):
self.behaviors = BehaviorTree(
Selector([
Sequence([
CheckPlayerNearby(radius=16),
PathfindToPlayer(),
AttackPlayer()
]),
Sequence([
Wait(random.randint(20, 100)),
MoveToRandomPosition(radius=10)
])
])
)
🗺️ Roadmap
Short-Term
Medium-Term
Long-Term
🤝 Contributing
We welcome your contributions! Please see our Contributing Guide to get started:
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to your 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.