LoL Data MCP Server
Provides real-time, structured access to League of Legends game data, including champions, items, abilities, game mechanics, and patch information.
🚧 PROJECT UNDER MAJOR RESTRUCTURE 🚧
LoL Data MCP Server is currently undergoing comprehensive restructuring and enhancement. This project will cover significantly more functionality than originally planned.
🔄 Current Status: Major Expansion in Progress
This project is being actively restructured to become a comprehensive League of Legends data ecosystem that will include:
🎯 Planned Coverage Areas (Under Development)
Phase 1: Core Data Infrastructure ⚡
- Champion Data System: Complete champion statistics, abilities, and patch history
- Item Data System: Item statistics, build paths, and patch tracking
- Runes & Masteries: Complete rune system integration
- Game Mechanics: Damage calculations, scaling formulas, and interactions
Phase 2: Advanced Analytics 📊
- Meta Analysis: Patch-by-patch meta evolution tracking
- Build Optimization: AI-powered optimal builds for different scenarios
- Champion Synergies: Advanced team composition analysis
- Performance Metrics: Win rates, pick/ban statistics, and trend analysis
Phase 3: AI Integration 🤖
- Training Data Generation: Structured datasets for machine learning
- Game State Recognition: Real-time game state parsing and analysis
- Decision Support: AI-powered recommendations for in-game decisions
- Simulation Environment: Complete LoL simulation for AI training
Phase 4: Real-Time Services ⚡
- Live Match Data: Real-time match tracking and analysis
- Player Analytics: Individual player performance tracking
- Meta Predictions: AI-powered meta shift predictions
- Community Integration: Discord bots, web APIs, and mobile apps
Phase 5: Advanced Features 🚀
- Video Analysis: Automatic highlight detection and analysis
- Voice Integration: Voice-activated champion information and builds
- AR/VR Support: Immersive data visualization for coaching
- Esports Analytics: Professional match analysis and statistics
🛠️ Technical Scope Expansion
Data Sources Integration
- League of Legends Wiki: Primary source for comprehensive game data
- Riot Games API: Official live data and statistics
- Community Platforms: Reddit, Discord, and forums for meta insights
- Esports Platforms: Professional match data and analytics
- Streaming Platforms: Popular streamer builds and strategies
Technology Stack Enhancement
- Backend: FastAPI, WebSocket, async/await patterns
- Data Processing: BeautifulSoup, Selenium, pandas, numpy
- AI/ML: TensorFlow, PyTorch, scikit-learn for analytics
- Caching: Redis for high-performance data caching
- Database: PostgreSQL for structured data, MongoDB for flexible schemas
- API Integration: RESTful APIs, GraphQL, WebSocket real-time updates
Integration Capabilities
- IDE Integration: Cursor, VS Code, JetBrains via MCP protocol
- Discord Bots: Real-time champion information and builds
- Web Applications: React/Vue frontends for data visualization
- Mobile Apps: React Native for on-the-go access
- CLI Tools: Command-line utilities for developers
- Game Overlays: In-game information overlays
🎯 Project Timeline
Current Phase: Core Infrastructure Development
Expected Completion: Rolling releases with major milestones every 2-4 weeks
Full Feature Set: Estimated 6-12 months for complete ecosystem
🔗 Related Projects
This MCP server will serve as the data backbone for:
- LoL Simulation Environment: AI training environments
- Taric AI Agent: Specialized support champion AI
- Community Tools: Discord bots, web apps, and mobile applications
- Research Projects: Academic and professional esports analytics
📋 Development Status
✅ Currently Implemented:
- Basic MCP server infrastructure
- Champion statistics scraping (with level-specific data)
- Champion abilities extraction
- Item patch history tracking
- Real-time wiki data integration
🔄 Under Active Development:
- Advanced item data system
- Comprehensive patch tracking
- Enhanced data accuracy and validation
- Performance optimization and caching
📋 Planned Features:
- Complete runes and masteries system
- Build recommendation engine
- Meta analysis and tracking
- Real-time match integration
- AI-powered insights and recommendations
⚡ This project represents a significant expansion beyond the original scope and will become a comprehensive League of Legends data ecosystem serving multiple AI, analytics, and community applications.
🚀 Stay tuned for regular updates as we build the most comprehensive LoL data service available.
相关服务器
COTI Blockchain MCP
Interact with the COTI blockchain for private token and NFT operations, including ERC20 and ERC721, with privacy features.
Dune Analytics
Access Dune Analytics data for AI agents, including DEX metrics, EigenLayer stats, and Solana token balances.
SolanaBot
Interact with the Solana blockchain to check balances, send SOL, and airdrop SOL.
MariaDB / MySQL
Access and manage MariaDB or MySQL databases using an MCP server.
Local FAISS
About Local FAISS vector store as an MCP server – drop-in local RAG for Claude / Copilot / Agents.
PostgreSQL & Google Sheets
MCP servers for interacting with PostgreSQL databases and Google Sheets.
MCP-MySQL-Ops
You are working with the MCP MySQL Operations Server, a powerful tool that provides comprehensive MySQL database monitoring and analysis capabilities through natural language queries. This server offers 19 specialized tools for database administration, performance monitoring, and system analysis.
Tabular MCP Server
An MCP server for local Tabular Models like PowerBI. It allows LLM clients to debug, analyze, and compose DAX queries by connecting to a local Tabular model instance.
Opera Omnia
Access a rich collection of JSON datasets for games, storytelling, and bot development from the Opera Omnia project.
MCP Qdrant Codebase Embeddings
Uses Qdrant vector embeddings to understand semantic relationships in codebases.