Manually initiate a learning cycle to analyze patterns, improve machine learning models, and enhance predictive capabilities within the MCP Self-Learning Server.
Provides comprehensive running performance calculations including VDOT, training paces, race time predictions, velocity markers, and heart rate zones using Jack Daniels, Greg McMillan, and Riegel methodologies.
A learning-focused MCP server that demonstrates how to build arithmetic tools for AI assistants, currently featuring addition functionality with structured input/output.
Generates personalized learning paths by integrating with YouTube, Google Drive, and Notion to create comprehensive learning experiences based on user goals.