PubMed MCP Server

# 🚀 PubMed MCP Server - Production Roadmap This roadmap outlines the path to making this PubMed MCP server a **world-class, production-ready tool** that researchers and developers will love to use. --- ## 🎯 **Phase 1: Core Stability & Quality** *(High Priority - 1-2 weeks)* ### 🧪 **Testing & Coverage** - [ ] **Increase test coverage from ~50% to 85%+** - [ ] Add integration tests for real PubMed API calls (with rate limiting) - [ ] Add comprehensive error handling tests - [ ] Add performance/load testing for cache and rate limiter - [ ] Add mock tests for all network failures and edge cases - [ ] Test citation formatting with real PubMed data samples - [ ] **Add property-based testing** - [ ] Use `hypothesis` library for testing edge cases - [ ] Test search query building with random inputs - [ ] Test PMID validation with various formats ### 🔧 **Code Quality & Linting** - [ ] **Fix all linting issues** (currently 149+ errors) - [ ] Remove all unused imports - [ ] Add missing type hints everywhere - [ ] Fix long lines and formatting issues - [ ] Resolve mypy type checking errors - [ ] Add docstrings to all missing functions - [ ] **Enhanced static analysis** - [ ] Add `bandit` for security scanning - [ ] Add `pylint` for additional code quality checks - [ ] Add `vulture` to find dead code ### 🛡️ **Error Handling & Resilience** - [ ] **Robust error handling** - [ ] Graceful handling of network timeouts - [ ] Proper error messages for invalid API keys - [ ] Fallback mechanisms for PubMed API failures - [ ] Input validation for all user parameters --- ## 🚀 **Phase 2: Performance & Scalability** *(Medium Priority - 2-3 weeks)* ### ⚡ **Performance Optimization** - [ ] **Advanced caching strategies** - [ ] Redis support for distributed caching - [ ] Cache warming for popular searches - [ ] Intelligent cache invalidation - [ ] Memory usage monitoring and optimization - [ ] **Async optimization** - [ ] Concurrent processing for batch operations - [ ] Connection pooling for HTTP requests - [ ] Streaming for large result sets ### 📊 **Monitoring & Observability** - [ ] **Comprehensive logging** - [ ] Structured logging with JSON format - [ ] Request/response logging for debugging - [ ] Performance metrics logging - [ ] Error tracking and alerting - [ ] **Health checks & metrics** - [ ] `/health` endpoint for monitoring - [ ] Prometheus metrics export - [ ] Rate limit monitoring - [ ] Cache hit rate tracking --- ## ✨ **Phase 3: Enhanced Features** *(Medium Priority - 3-4 weeks)* ### 🔍 **Advanced Search Capabilities** - [ ] **Smart search features** - [ ] Auto-completion for journals and authors - [ ] Search suggestions and typo correction - [ ] Saved searches and search history - [ ] Bulk operations (multiple PMIDs at once) - [ ] **Enhanced data processing** - [ ] Full-text article processing (when available) - [ ] Automatic abstract summarization - [ ] Citation network analysis - [ ] Duplicate detection and merging ### 📋 **Export & Integration** - [ ] **Multiple export formats** - [ ] CSV export for spreadsheet analysis - [ ] JSON-LD for semantic web integration - [ ] XML export for academic systems - [ ] Direct integration with reference managers - [ ] **Data enrichment** - [ ] Impact factor and journal metrics - [ ] Author h-index and citation metrics - [ ] Conference/journal ranking data - [ ] Open access status detection --- ## 🌐 **Phase 4: Production Deployment** *(High Priority - 1-2 weeks)* ### 🐳 **Container & Deployment** - [ ] **Production Docker setup** - [ ] Multi-stage optimized Dockerfile - [ ] Non-root user for security - [ ] Health checks in container - [ ] Docker Compose for local development - [ ] **Cloud deployment options** - [ ] AWS Lambda/ECS deployment guides - [ ] Google Cloud Run deployment - [ ] Heroku one-click deploy - [ ] Kubernetes manifests ### 🔐 **Security & Configuration** - [ ] **Security hardening** - [ ] Input sanitization and validation - [ ] Rate limiting per API key - [ ] CORS configuration - [ ] Security headers - [ ] **Configuration management** - [ ] Environment-specific configs - [ ] Secret management best practices - [ ] Configuration validation - [ ] Runtime configuration updates --- ## 📚 **Phase 5: Documentation & Community** *(High Priority - 1-2 weeks)* ### 📖 **Documentation** - [ ] **Comprehensive documentation** - [ ] Interactive API documentation (Swagger/OpenAPI) - [ ] Getting started tutorials - [ ] Advanced usage examples - [ ] Troubleshooting guide - [ ] **Developer experience** - [ ] SDK/client libraries (Python, JavaScript, R) - [ ] Postman collection - [ ] Video tutorials and demos - [ ] Code examples for common use cases ### 🌟 **Community & Open Source** - [ ] **Open source best practices** - [ ] Contributor guidelines - [ ] Code of conduct - [ ] Issue templates - [ ] Pull request templates - [ ] **Release management** - [ ] Semantic versioning - [ ] Automated releases with GitHub Actions - [ ] Changelog generation - [ ] PyPI package publication --- ## 🏆 **Phase 6: Advanced Features** *(Lower Priority - Future)* ### 🤖 **AI & ML Integration** - [ ] **Smart features** - [ ] AI-powered search query suggestions - [ ] Automatic research paper categorization - [ ] Trend analysis and predictions - [ ] Research collaboration recommendations ### 🔌 **Integrations** - [ ] **Third-party integrations** - [ ] ORCID integration for author profiles - [ ] CrossRef integration for citations - [ ] arXiv integration for preprints - [ ] Google Scholar integration --- ## 📋 **Current Status Checklist** ### ✅ **Completed** - [x] Basic MCP server implementation - [x] Comprehensive tool set (13 tools) - [x] Docker containerization - [x] CI/CD pipeline with GitHub Actions - [x] Modern Python packaging (pyproject.toml) - [x] Pre-commit hooks setup - [x] Basic test suite (83 tests) - [x] Code formatting with Black - [x] Type hints foundation ### 🚧 **In Progress** - [x] CI/CD pipeline (fixing final issues) - [ ] Code quality improvements ### ⏳ **Next Priority** 1. **Fix all linting issues** (Phase 1) 2. **Increase test coverage to 85%+** (Phase 1) 3. **Add comprehensive documentation** (Phase 5) 4. **Production deployment setup** (Phase 4) --- ## 🎯 **Success Metrics** - **Code Quality**: 0 linting errors, 85%+ test coverage, A+ code grade - **Performance**: <200ms average response time, 99.9% uptime - **Community**: 100+ GitHub stars, 10+ contributors, 5+ integrations - **Usage**: 1000+ API calls/day, 50+ active users --- ## 🚀 **Quick Wins (This Week)** 1. **Fix all current linting issues** - Will dramatically improve code quality 2. **Add missing docstrings** - Better developer experience 3. **Increase test coverage** - Focus on critical paths first 4. **Add real PubMed integration tests** - Catch real-world issues 5. **Improve documentation** - Make it easier for others to adopt **Estimated time to production-ready**: **4-6 weeks** following this roadmap. This will result in a **best-in-class PubMed MCP server** that researchers and developers will love! 🌟