Statuspage vs Health Export MCP

Statuspage tools

No tool names declared yet. Check the project README from the listing page.

Health Export MCP tools 14

• get_mcp_statusHealth check: data source, how many metrics/workouts are available, which optional context files exist, and the most recent data date. Call this first to confirm the bridge is connected.
• list_metricsList every available Apple Health metric with its unit, day count, and date range. Use this to discover metric names before querying.
• get_health_metricsGet values for a metric (or all metrics) over an optional date range, with an aggregate (avg/sum/min/max/latest). The core data-retrieval tool. Every result carries a `coverage` block giving the metric's real firstDate/lastDate/days: check it before trusting a long window, and note that `aggregate` is always computed over the full range even when `points` are rolled up. Single-metric answers also list any logged point events inside the window as segmentBoundaries.
• get_trendsCompare the most recent N-day window against the prior N days for a metric: change, percent change and direction (up/down/flat). Also returns `daysAvailable` and `windowSatisfied`: if windowSatisfied is false the file does not hold enough history for the window you asked for, and the comparison is over less data than requested. Logged point events inside the compared span are listed as segmentBoundaries.
• compare_periodsCompare a metric between two arbitrary date periods (A vs B): each aggregate plus the change and percent change. Pass periodA/periodB explicitly, or pass anchor {eventId, days} to build both periods around a logged event (the before/after question, with the event day excluded from both sides).
• get_structured_exportReturn clean structured JSON for the chosen metrics/date range. Paginated: the result carries `nextCursor` when more metrics remain; pass it back as `cursor` for the next page. Prefer naming the metrics you need and a date range; calling it bare over a full history is a lot of data.
• get_intradayThe current hour-by-hour window from the iOS app's HOURLY automations (health-intraday.json, app 1.4+): each metric's hourly points plus its latest value. The file is REPLACED on every hourly run, so this is a live within-day view, not history; use get_health_metrics for day-level questions. Returns available:false with setup guidance when no hourly automation has delivered yet.
• query_health_dataNatural-language convenience: pass a question and get routed structured results. Prefer the specific tools above when you can, and call list_metrics first to see how much history exists, since this tool answers over whatever the file holds.
• list_eventsLogged context events from health-events.json: medication starts, habit changes, doctor visits, life events, shift blocks, episodes, travel, and any type a newer app adds. Optional {type, tag, start, end} filters; a range event matches a window it overlaps. Sorted ascending by date. Returns available:false when the file was never exported; absence means nothing was exported, not that nothing happened.
• get_profileThe context fields the user explicitly opted in to sharing (health-profile.json): conditions, medications, goals, allergies, notes. Returns the fields plus a presentFields list. An absent field was withheld by the user or never enabled; absence must never be read as "none".
• get_workoutsQuery the workouts cache with {activityType (a name like Running, or a raw HealthKit id like 37), start, end} filters and pagination ({limit} default 50 max 200, {cursor} from a previous nextCursor). Records are returned exactly as stored, including the newer optional keys (avgHeartRate, maxHeartRate, running dynamics, cycling power, intervals, hasRoute) when the app exported them; older caches simply lack those keys and nothing is fabricated. Also returns summary {count, byActivityType} over everything that matched.
• get_sleep_sessionsClustered sleep sessions from health-sessions.json with {start, end, day} filters. Sessions are attributed to the WAKING day, matching the daily cache's sleep_analysis, so the two surfaces never disagree; a split night appears as multiple sessions with the same day, returned as-is. Timestamps carry the local UTC offset at the time of the sample.
• +2 more on the listing page