Developed an AI Insights Analytics Toolset within the harness/mcp-server repository to streamline analytics for Cursor and Windsurf metrics. Focused on backend and API development using Go, the work involved consolidating multiple analytics tools into a unified sei_get_ai_impact API endpoint with type parameters, reducing the tooling surface from eleven to nine. This refactoring improved maintainability and performance while enhancing observability and data quality for usage metrics. Comprehensive testing and documentation updates were implemented to ensure reliability. The resulting solution enabled faster, data-driven decision-making and reduced maintenance costs by eliminating redundant endpoints and improving the clarity of analytics tooling for the team.