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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Log a workout by providing the date, exercises with sets, and perceived effort.
Calculate safe training weights based on the exercise name, base weight, days since surgery, recent pain level, and recent RPE.
Log a meal by specifying the meal type, foods with their amounts, protein, calorie content, hunger level, and satisfaction level.
Check daily nutrition targets for a specified date.
Create a journal entry with entry type, content, mood, energy, sleep quality, stress level, and tags.
Analyze journal entries within a specified date range.