The Design Patterns MCP Server provides intelligent design pattern recommendations through semantic search and natural language queries, accessing a comprehensive catalog of 555+ patterns across 20+ categories.
Core Capabilities:
- Natural language pattern discovery: Find relevant patterns using problem descriptions with confidence-scored recommendations 
- Advanced search options: Perform keyword, semantic, or hybrid searches with filtering by categories (GoF, Architectural, Microservices, React, AI/ML, Security, etc.) and programming languages 
- Detailed pattern information: Access comprehensive details including multi-language code examples, relationships, and use cases for any specific pattern 
- Catalog statistics: Query total pattern counts with optional category breakdowns 
- High-performance operations: Fast vector search using sqlite-vec with LRU caching and object pooling, delivering 30-40% faster repeated queries 
- AI assistant integration: Compatible with MCP clients like Claude Code and Cursor for seamless workflow integration 
Uses SQLite with vector extensions for efficient semantic search and storage of design pattern embeddings and metadata
Design Patterns MCP Server ๐ฏ
An intelligent MCP (Model Context Protocol) server that provides design pattern recommendations using semantic search and vector embeddings. This project offers access to a comprehensive catalog of 555+ design patterns through a natural language interface.
๐ Overview
The Design Patterns MCP Server is a specialized server that integrates with AI assistants (like Claude, Cursor) to provide intelligent design pattern recommendations. It uses advanced semantic search technologies to find the most appropriate patterns based on natural language problem descriptions.
โจ Key Features
- ๐ Intelligent Semantic Search: Find patterns using natural problem descriptions 
- ๐ Comprehensive Catalog: 555+ patterns organized in 20+ categories 
- ๐ฏ Contextual Recommendations: Suggestions based on programming language and domain 
- โก Vector Search: Uses SQLite with vector extensions for efficient search 
- ๐ Multi-language: Support for multiple programming languages 
- ๐ง MCP Integration: Compatible with Claude Code, Cursor and other MCP clients 
- ๐ High Performance: Object Pool pattern prevents memory leaks, 30-40% faster queries 
- ๐พ Smart Caching: LRU cache with 85%+ hit rate 
- ๐๏ธ SOLID Architecture: Clean, maintainable, and testable codebase 
๐ Recent Improvements (v0.2.1)
Architecture Refactoring (October 2025)
- โ Object Pool Pattern: Eliminates memory leaks with bounded prepared statements 
- โ Service Layer: Centralized business logic with - PatternService
- โ Facade Pattern: Simplified handlers via - PatternHandlerFacade
- โ Dependency Injection: Full DI Container integration for testability 
- โ Performance: 30-40% faster on repeated queries with smart caching 
- โ Code Quality: 40% reduction in main server file (704โ422 lines) 
- โ Pattern Catalog: Expanded to 555+ patterns with code examples 
๐๏ธ Available Pattern Categories
- GoF Patterns: Classic patterns (Creational, Structural, Behavioral) 
- Architectural Patterns: MVC, MVP, MVVM, Clean Architecture, Hexagonal 
- Microservices Patterns: Circuit Breaker, Event Sourcing, CQRS, Saga 
- Cloud Patterns: Auto-scaling, Load Balancing, Service Discovery 
- AI/ML Patterns: Model Training, RAG, Few-Shot Learning, Continual Learning 
- React Patterns: Hooks, Server Components, Suspense, React 19 features 
- Enterprise Patterns: Repository, Unit of Work, Dependency Injection 
- Security Patterns: Authentication, Authorization, Data Protection 
- Performance Patterns: Caching, Lazy Loading, Object Pool, Connection Pooling 
- Concurrency Patterns: Producer-Consumer, Thread Pool, Actor Model 
- Integration Patterns: Message Queue, Event Bus, API Gateway 
- Data Access Patterns: Active Record, Data Mapper, Query Object 
- Testing Patterns: Test Double, Page Object, Builder Pattern for tests 
- Functional Patterns: Monads, Functors, Higher-Order Functions 
- Reactive Patterns: Observer, Publisher-Subscriber, Reactive Streams 
- DDD Patterns: Aggregate, Value Object, Domain Service, Bounded Context 
- Game Development Patterns: State Machine, Component System, Object Pool 
- Mobile Patterns: Model-View-Intent, Redux-like patterns, Offline-First 
- IoT Patterns: Device Twin, Telemetry Ingestion, Edge Processing 
- Blockchain/Web3 Patterns: DeFi, NFT, DAO, Cross-chain 
- Anti-Patterns: Practices to avoid and their solutions 
๐๏ธ Project Architecture
Refactored Architecture (v0.2.x)
๐ง Main Components
Core Services
- DatabaseManager: SQLite operations with Object Pool (prevents memory leaks) 
- StatementPool: LRU-based pool for prepared statements (max 100) 
- CacheService: In-memory LRU cache with TTL and metrics 
Business Logic
- PatternService: Service Layer orchestrating pattern operations 
- PatternRepository: Data access abstraction (Repository Pattern) 
- SemanticSearchService: Semantic search with embeddings 
- PatternMatcher: Pattern matching and ranking logic 
Integration
- PatternHandlerFacade: Facade simplifying MCP handlers 
- VectorOperationsService: Vector search using sqlite-vec 
- LLMBridgeService: Interface for language models (optional) 
- EmbeddingServiceAdapter: Adapter for embedding services 
Infrastructure
- SimpleContainer: Dependency Injection container 
- MigrationManager: Database migrations 
- PatternSeeder: Initial data seeding 
๐ Installation and Setup
Prerequisites
- Node.js >= 18.0.0 
- npm >= 8.0.0 or Bun >= 1.0.0 
Installation
MCP Configuration
Add to your MCP configuration file (.mcp.json or Claude Desktop config):
๐ Usage
Finding Patterns with Natural Language
Use natural language descriptions to find appropriate design patterns through Claude Code:
For object creation problems:
- "I need to create complex objects with many optional configurations" 
- "How can I create different variations of similar objects?" 
- "What pattern helps with step-by-step object construction?" 
For behavioral problems:
- "I need to notify multiple components when data changes" 
- "How to decouple command execution from the invoker?" 
- "What pattern helps with state-dependent behavior?" 
For architectural problems:
- "How to structure a microservices communication system?" 
- "What pattern helps with distributed system resilience?" 
- "How to implement clean separation between layers?" 
For React development:
- "How to manage state in React 18/19?" 
- "What patterns work with React Server Components?" 
- "How to optimize React performance?" 
MCP Tool Functions
- find_patterns: Semantic search for patterns using problem descriptions - Returns ranked recommendations with confidence scores 
- Supports category filtering and programming language preferences 
 
- search_patterns: Keyword or semantic search with filtering options - Supports hybrid search (keyword + semantic) 
- Filter by category, tags, complexity 
 
- get_pattern_details: Get comprehensive information about specific patterns - Includes code examples in multiple languages 
- Shows similar patterns and relationships 
- Displays implementations and use cases 
 
- count_patterns: Statistics about available patterns by category - Optional detailed breakdown by category 
 
๐ ๏ธ Available Commands
๐ฏ Usage Examples
Problem-Based Pattern Discovery
Distributed Systems:
- "I need a pattern for handling service failures gracefully" โ Circuit Breaker, Bulkhead 
- "How to implement eventual consistency in distributed data?" โ Event Sourcing, CQRS 
- "What pattern helps with service discovery and load balancing?" โ Service Registry, API Gateway 
Data Validation:
- "I need to validate complex business rules on input data" โ Specification Pattern 
- "How to compose validation rules dynamically?" โ Chain of Responsibility 
- "What pattern separates validation logic from business logic?" โ Strategy Pattern 
Performance Optimization:
- "I need to cache expensive computations efficiently" โ Cache-Aside, Write-Through 
- "How to implement lazy loading for large datasets?" โ Lazy Loading, Virtual Proxy 
- "What pattern helps with connection pooling?" โ Object Pool Pattern 
Category-Specific Searches
Enterprise Applications:
- "Show me enterprise patterns for data access" โ Repository, Unit of Work, Data Mapper 
- "What patterns help with dependency injection?" โ DI Container, Service Locator 
- "How to implement domain-driven design?" โ Aggregate, Value Object, Bounded Context 
Security Implementation:
- "I need authentication and authorization patterns" โ RBAC, OAuth 2.0, JWT 
- "What patterns help with secure data handling?" โ Encryption at Rest, Defense in Depth 
- "How to implement role-based access control?" โ RBAC Pattern, Policy-Based Access 
๐ง Advanced Configuration
Environment Variables
Using the Refactored Server
Performance Monitoring
๐ Performance and Scalability
Performance Characteristics
- Vector Search: Uses sqlite-vec for efficient search in large volumes 
- Object Pool: Bounded prepared statement cache (max 100) prevents memory leaks 
- Intelligent Cache: LRU cache with 85%+ hit rate in production 
- Query Performance: 30-40% faster on repeated queries vs uncached 
- Optimized Indexes: Specific indexes for different search types 
- Pagination: Support for large result sets 
- Metrics: Built-in performance and usage metrics 
Benchmarks (from tests)
๐งช Testing
The project includes a comprehensive test suite with 116 passing tests:
- Contract Tests: Validate MCP protocol compliance 
- Integration Tests: Test interaction between components 
- Performance Tests: Evaluate search and vectorization performance 
- Unit Tests: Test individual components in isolation 
Test Coverage
- MCP Protocol: โ 100% 
- Core Services: โ 95%+ 
- Performance: โ Comprehensive benchmarks 
- Database: โ Full migration & seeding tests 
๐๏ธ Architecture Patterns Used
This project practices what it preaches by implementing:
| Pattern | Location | Purpose | 
| Repository | 
 | Data access abstraction | 
| Service Layer | 
 | Business logic orchestration | 
| Object Pool | 
 | Resource management | 
| Facade | 
 | Simplified interface | 
| Dependency Injection | 
 | Inversion of control | 
| Strategy | 
 | Interchangeable algorithms | 
| Factory | 
 | Object creation | 
| Singleton | Via DI Container | Single instance management | 
| Adapter | 
 | External service integration | 
๐ค Contributing
We welcome contributions! Here's how:
- Fork the project 
- Create a feature branch ( - git checkout -b feature/amazing-feature)
- Make your changes following our code style 
- Run tests ( - npm test) and ensure they pass
- Run linting ( - npm run lint:fix)
- Commit your changes ( - git commit -am 'Add amazing feature')
- Push to the branch ( - git push origin feature/amazing-feature)
- Open a Pull Request 
Development Guidelines
- Follow SOLID principles 
- Write tests for new features 
- Update documentation 
- Use TypeScript strict mode 
- Follow existing code patterns 
๐ License
This project is licensed under the MIT License. See LICENSE for details.
๐ Useful Links
๐ Support
- ๐ Issues: Report bugs through GitHub Issues 
- ๐ฌ Discussions: Join GitHub Discussions 
- ๐ง Email: apolosan@protonmail.com 
- ๐ Documentation: Comprehensive architecture and refactoring details available in project documentation 
๐ Acknowledgments
- Design patterns from the software engineering community 
- MCP protocol by Anthropic 
- SQLite and sqlite-vec for efficient storage and search 
- Open source contributors 
Version: 0.2.1
Last Updated: October 2025
Patterns: 555+
Tests: 116 passing
Performance: 30-40% improvement vs v0.1.x
local-only server
The server can only run on the client's local machine because it depends on local resources.
Provides intelligent design pattern recommendations using semantic search through a comprehensive catalog of 200+ patterns across 20 categories. Users can describe programming problems in natural language to discover appropriate design patterns with contextual recommendations.
- ๐ Overview
- ๐๏ธ Project Architecture
- ๐ Installation and Setup
- ๐ Usage
- ๐ ๏ธ Available Commands
- ๐ฏ Usage Examples
- ๐ง Advanced Configuration
- ๐ Performance and Scalability
- ๐งช Testing
- ๐๏ธ Architecture Patterns Used
- ๐ค Contributing
- ๐ License
- ๐ Useful Links
- ๐ Support
- ๐ Acknowledgments