This personal MCP server, developed for health and well-being tracking, integrates with pandas for data analysis and pydantic for data validation. It uses a command-line interface built with Click and rich for enhanced terminal output. The implementation is designed for individuals who want to track and analyze their personal health data using AI assistance, allowing for natural language queries and visualization of trends. It's particularly suited for users who prefer local data storage and processing, offering a balance between privacy and powerful analysis capabilities.
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Highlight AILog a workout with details such as date, exercises, sets, reps, and perceived effort.
Calculate safe training weights based on parameters including exercise, base weight, days since surgery, recent pain level, and recent RPE.
Log a meal with meal type, foods, hunger level, and satisfaction level.
Check nutrition targets for a specified date.
Create a journal entry with content, mood, energy, sleep quality, stress level, and tags.
Analyze journal entries between a specified start date and end date.
