MCP Meetup-Claude Integration Server

# ADR-002: Dual API Strategy for Meetup.com Integration ## Status Accepted ## Context Meetup.com provides both REST and GraphQL APIs for accessing event data. Each has different capabilities, limitations, and use cases. We need to decide how to leverage these APIs effectively in our MCP server. ## Decision We will implement a dual API strategy that primarily uses the REST API with GraphQL as a fallback and enhancement mechanism. ## Rationale ### REST API Analysis: **Advantages:** - Simpler authentication and request structure - Better documented with clear examples - More stable and widely supported - Lower complexity for basic event searches - Familiar HTTP patterns for debugging **Limitations:** - Less flexible query capabilities - May require multiple requests for complex data - Fixed response structure ### GraphQL API Analysis: **Advantages:** - More flexible and precise queries - Single request can fetch complex nested data - Better performance for specific data requirements - Future-proof query capabilities **Limitations:** - More complex authentication requirements - Steeper learning curve - Less stable (evolving schema) - Harder to debug and monitor ## Implementation Strategy ### Primary: REST API - Use REST API as the primary method for event discovery - Implement in `search_events_rest()` method - Handle standard use cases: location-based search, keyword filtering, time ranges - Simpler error handling and debugging ### Secondary: GraphQL API - Implement GraphQL as fallback when REST fails or returns insufficient results - Use for enhanced queries requiring complex nested data - Implement in `search_events_graphql()` method - Leverage for future advanced features ### Fallback Logic: ```python # Primary attempt with REST events = await self.search_events_rest(query) # Fallback to GraphQL if needed if not events: events = await self.search_events_graphql(query) ``` ## Architecture Impact ### Event Discovery Engine: - Unified `EventQuery` model works with both APIs - Separate parsing methods for each API response format - Common `MeetupEvent` model for consistent output - Intelligent query parameter mapping for each API ### Error Handling: - Independent error handling for each API - Graceful degradation when one API fails - Logging and monitoring for both APIs - User-friendly error messages regardless of API used ### Performance Considerations: - REST API calls are typically faster and more reliable - GraphQL used only when necessary to avoid complexity overhead - Parallel API calls considered for future optimization - Caching strategy works with both APIs ## Benefits 1. **Reliability**: If one API has issues, the other provides backup 2. **Flexibility**: Can choose optimal API for specific query types 3. **Future-proofing**: Ready to leverage GraphQL advantages as it matures 4. **Performance**: Use simpler REST for most cases, GraphQL for complex needs 5. **Debugging**: Easier troubleshooting with REST, advanced queries with GraphQL ## Tradeoffs ### Positive: - Higher reliability and availability - Better performance characteristics - More comprehensive event discovery - Future flexibility for advanced features ### Negative: - Increased code complexity (two API implementations) - More testing surface area - Potential inconsistencies between APIs - Additional maintenance overhead ### Mitigation: - Unified data models ensure consistent output - Comprehensive testing for both API paths - Clear logging to track which API is used - Documentation covers both API behaviors ## Future Considerations ### API Evolution: - Monitor Meetup.com's API roadmap and deprecation notices - Be prepared to adjust primary/secondary roles based on API stability - Consider GraphQL-first approach if it becomes more stable ### Feature Expansion: - Advanced filtering may favor GraphQL - Real-time features might require GraphQL subscriptions - Bulk operations might benefit from GraphQL batch queries ### Performance Optimization: - Implement request caching that works with both APIs - Consider parallel API calls for comprehensive results - Monitor API response times and adjust strategy accordingly ## Monitoring and Success Metrics - Track success/failure rates for each API - Monitor response times and data quality - Measure user satisfaction with event discovery results - Assess need for GraphQL-first queries based on usage patterns --- **Date**: 2025-07-27 **Author**: Dan Shields **Dependencies**: ADR-001 (MCP Protocol Choice)