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 exercises, sets, and perceived effort. Parameters: date (string), exercises (list of objects), perceived_effort (integer)
Calculate safe training weights based on rehabilitation considerations. Parameters: exercise (string), base_weight (integer), days_since_surgery (integer), recent_pain_level (integer), recent_rpe (integer)
Log a meal with details about food items and hunger levels. Parameters: meal_type (string), foods (list of objects), hunger_level (integer), satisfaction_level (integer)
Check nutrition targets for a specific date. Parameters: date (string)
Create a journal entry with mood, energy, and other personal metrics. Parameters: entry_type (string), content (string), mood (integer), energy (integer), sleep_quality (integer), stress_level (integer), tags (list of strings)
Analyze journal entries between specific dates. Parameters: start_date (string), end_date (string)
