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PAP Analytics MCP

PAP Analytics MCP

by drew2323

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      Query Apple Health export data with an LLM via a semantic layer that avoids common data traps, enabling accurate natural-language queries about health metrics. Optionally imports CPAP therapy data for correlation.
      3
      MIT
    • F
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      Enables AI assistants to access and analyze Oura Ring health data including sleep, readiness, activity, and stress metrics. Supports customizable queries, correlation analysis, and visualization capabilities for comprehensive health insights.
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    • A
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      Enables AI agents to query a local SQLite export of Garmin Connect data — daily summaries, sleep stages, HRV, readiness, activities and intraday heart rate, stress, Body Battery and SpO2 — through tools like get_day, compare_periods, get_sleep_detail, get_timeseries and a read-only run_sql. This lets an agent compare periods against personal baselines while keeping raw payloads, credentials and network ports out of reach.
      MIT
    • F
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      Enables AI assistants to query health metrics such as activity, blood pressure, glucose, heart rate, sleep, and SpO2 from a PostgreSQL-backed wellness database, returning structured data and summaries through MCP tools.
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      Enables AI assistants to analyze sleep quality, compare nights, generate reports, and get personalized improvement tips using Sleepon sleep tracker data.
      MIT
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      Enables users to query recovery, sleep, HRV, strain, workouts, and personal health analytics in natural language through supported AI assistants, using read-only tools for daily status, baselines, trends, and period comparisons.
      18 npm
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