Personal Health Tracker
Summary
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.
Available Actions(6)
log_workout
Log a workout with details including date, exercises, sets, reps, and perceived effort.
calculate_training_weights
Calculate safe training weights based on exercise, base weight, days since surgery, recent pain level, and recent RPE.
log_meal
Log a meal with details including meal type, foods, hunger level, and satisfaction level.
check_nutrition_targets
Check daily nutrition targets for a specific date.
create_journal_entry
Create a journal entry with details including entry type, content, mood, energy, sleep quality, stress level, and tags.
analyze_journal_entries
Analyze journal entries between a specified start and end date.
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