apple-health-export-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AH_DB_PATH | Yes | Path to the SQLite database file containing Apple Health data. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_typesA | List which health metrics exist in this export, with row counts and date spans. Call this first to discover the exact |
| list_sourcesA | List which sources/devices wrote a metric, with counts and date spans. Use it to see why a |
| get_quantityA | Aggregate a numeric metric (steps, weight, heart rate, energy…) over a date range. Call |
| get_sleepA | Per-night sleep stage durations (minutes), attributed to the wake-up day. Returns [{night, asleep_min, rem_min, deep_min, core_min, awake_min, in_bed_min}]. Older nights may report only in_bed_min (legacy devices lack stage detail). |
| get_workoutsA | Workout summary per activity type in a date range: count, total & avg minutes. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| daily_summary | A single day's health snapshot: steps, sleep, resting heart rate, workouts, energy. |
| weekly_review | Calendar-week review (Mon–Sun): training load, sleep, recovery, and a recommendation. |
| monthly_summary | A month in review: totals, averages, body-weight change, and trend. |
| yearly_summary | A year in review: big-picture fitness trajectory and milestones. |
| readiness_check | Should I train hard today? Based on last night's sleep and recent recovery markers. |
| sleep_report | Sleep deep-dive over a range: duration, stage breakdown, and consistency. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: get_quantity aggregates numeric metrics, get_sleep handles sleep stages, get_workouts summarizes workouts, list_sources lists devices, and list_types enumerates health metrics. No overlap in functionality.
All tools follow a consistent verb_noun pattern using snake_case (e.g., get_quantity, list_sources). There is no variation in style or convention.
With 5 tools, the server is well-scoped for a health data export interface. Each tool serves a distinct purpose without redundancy, and the count is neither too sparse nor too heavy.
The tool surface covers key health data access: numeric metrics (get_quantity), sleep (get_sleep), workouts (get_workouts), source discovery (list_sources), and type discovery (list_types). This set supports common queries without obvious gaps for the domain.