# health-export-mcp, Apple Health MCP server for AI agents

**Query your Apple Health data from Claude, ChatGPT, Cursor, OpenClaw, Hermes, and any other AI agent.**

`health-export-mcp` is an open-source, **zero-dependency** [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server that lets any MCP-compatible AI agent query your **Apple Health / HealthKit** data, **190 metrics** as clean JSON, in plain language. Local-first, read-only, no accounts, and no developer server in the path. It's the open-source server for the [MetricBridge](https://www.healthexport.dev) iOS app, **[available on the App Store](https://apps.apple.com/app/id6784185201)**.

<p align="center"><a href="https://apps.apple.com/app/id6784185201"><img alt="Download MetricBridge on the App Store" src="https://img.shields.io/badge/Download_on_the-App_Store-0D96F6?style=for-the-badge&logo=apple&logoColor=white" height="38" /></a></p>

<p align="center">
  <a href="https://glama.ai/mcp/servers/PhilipAD/health-export-mcp"><img alt="Glama MCP Server" src="https://glama.ai/mcp/servers/PhilipAD/health-export-mcp/badges/score.svg" /></a>
  <img alt="MCP" src="https://img.shields.io/badge/Model_Context_Protocol-server-6E56CF" />
  <img alt="zero dependencies" src="https://img.shields.io/badge/dependencies-0-2ea44f" />
  <img alt="Node ≥18" src="https://img.shields.io/badge/node-%E2%89%A518-339933?logo=node.js&logoColor=white" />
  <img alt="License: MIT" src="https://img.shields.io/badge/license-MIT-blue" />
  <img alt="works with Claude, Cursor, ChatGPT, OpenClaw, Hermes" src="https://img.shields.io/badge/works_with-Claude_·_Cursor_·_ChatGPT_·_OpenClaw_·_Hermes-111" />
</p>

<p align="center">
  <img src="assets/architecture.svg" alt="Apple Health exports to iCloud, a folder, or your LAN; health-export-mcp reads it and serves 16 query tools to your AI agent" width="100%" />
</p>

> Ask your agent: *"Compare my HRV this week vs last week and tell me if I'm recovering."*, it calls the tools and answers from your **actual numbers**.

---

## What is health-export-mcp?

It's an MCP server that turns your Apple Health export into a tool your AI agent can query in natural language, HRV, sleep, resting heart rate, steps, workouts, VO₂ max, and 180+ more.

- **Who it's for:** anyone who wants their AI to reason over their *real* health data instead of a stale CSV.
- **What it isn't:** a cloud service. There's no developer server in the path, your data goes only where *you* point it.
- **Setup:** point the server at your exported data and add it to your AI client.

> **Just exported and the Mac has not seen it yet?** iCloud can take a few minutes to sync the
> file across, so a check 60 seconds after tapping Run in the app can still show the old
> timestamp. `get_mcp_status` reports `lastDataDate` and the intraday `lastWrite`, which is the
> quickest way to tell "still syncing" from "never arrived".

> **Try it with no iPhone needed:** `node server.mjs --demo` serves a deterministic synthetic dataset (400 days, workouts, events, sleep sessions) with every answer watermarked as synthetic. Or run `npm test` to write a sample cache and exercise every tool.

---

## Connect Apple Health to your AI agent, Quickstart

### 1. Get your Apple Health data flowing

The companion iOS app **[MetricBridge](https://www.healthexport.dev)** exports your Apple Health data, read-only, automatic, private. For this MCP server, export to a destination it can read:

| Destination | Notes |
|---|---|
| **iCloud Drive** (default) | Your Mac reads the synced folder automatically |
| **Local folder** | Any folder that syncs to your Mac (Dropbox, Google Drive, OneDrive, …) |
| **LAN** (HTTP / WebSocket) | Direct push to the server, great over Tailscale |

> Using a non-MCP tool (ChatGPT, n8n, Home Assistant)? The app can also POST to a **webhook** those tools read directly, see [Works with](#works-with-claude-cursor-chatgpt-openclaw-hermes).

### 2. Add the server to your agent

**Fastest, auto-configure:**

```bash
git clone https://github.com/PhilipAD/health-export-mcp.git
cd health-export-mcp
node apply-mcp-config.mjs     # detects installed clients and writes the config for you
```

**Manual, Claude Desktop** (`~/Library/Application Support/Claude/claude_desktop_config.json`):

```json
{
  "mcpServers": {
    "health-export": {
      "command": "npx",
      "args": ["-y", "health-export-mcp"],
      "env": { "HEALTH_DATA_DIR": "~/Library/Mobile Documents/iCloud~ai~healthexport~app/Documents" }
    }
  }
}
```

> `npx` fetches the published package at run time (npm verifies package integrity), it runs anywhere, no clone or absolute path needed. Prefer to pin a vetted local checkout instead? Use `"command": "node", "args": ["REPLACE_WITH_ABSOLUTE_PATH/server.mjs"]`, get the path with `node -e "console.log(process.cwd()+'/server.mjs')"` inside the repo.
> Or skip JSON entirely, drag **`health-export.mcpb`** into **Claude Desktop → Settings → Extensions**.

**Cursor / VS Code:** `node gen-deeplinks.mjs` prints one-click install links.
**opencode / OpenClaw / Hermes:** see **[AGENTS.md](AGENTS.md)** for the exact block, same shape, one per client.

### 3. Ask your agent

Restart the client and try:

> *"Use health-export: what's my average HRV this week vs last week?"*

---

## Works with Claude, Cursor, ChatGPT, OpenClaw, Hermes

| Client / Agent | Integration | How |
|---|---|---|
| **Claude Desktop** | Native MCP | `.mcpb` bundle, or `mcpServers` block |
| **Cursor** | Native MCP | One-click deeplink, or `~/.cursor/mcp.json` |
| **opencode** | Native MCP | `opencode.json` `mcp` block |
| **OpenClaw** | Native MCP | Add the server block to your MCP config |
| **Hermes** | Native MCP | Add the server block to your agent's MCP config |
| **VS Code** (Copilot / Continue) | Native MCP | One-click deeplink |
| **ChatGPT · Gemini · Grok** | Webhook* | Consume the app's webhook export |
| **n8n · Home Assistant** | Webhook* | Trigger automations on the exported JSON |

<sub>*MCP clients query this server directly over stdio. ChatGPT / Gemini / Grok / n8n / Home Assistant don't speak MCP, they consume the same Apple Health data via the iOS app's token-authenticated **webhook** export.</sub>

---

## The 16 MCP tools

Full reference with request/response examples: **[healthexport.dev/mcp](https://www.healthexport.dev/mcp/#tools)**.

| Tool | What it does |
|---|---|
| `get_mcp_status` | Health check: source, metric/workout counts, which context files exist, latest data date, and a `freshness` summary. **Call first.** |
| `get_freshness` | How current the export is: `stale` against a stated threshold (26 h by default, `HEALTH_STALE_AFTER_HOURS`, or `maxAgeHours`), `age_hours`, `as_of`, `last_data_date`, per-file write times. Same rule as the `status --max-age` cron gate. |
| `list_metrics` | Every available metric with unit, day count, and date range. |
| `get_health_metrics` | Daily values for a metric (or all) over a date range + an aggregate (avg/sum/min/max/latest). Supports `filterDays` (restrict to days covered by logged events, with `negate`). |
| `get_trends` | Recent N-day window vs the prior N days: change, % change, direction. Supports `excludeTravelDays`. |
| `compare_periods` | A metric across two arbitrary date periods (A vs B), or around a logged event via `anchor: {eventId, days}` (the event day excluded from both sides). |
| `get_structured_export` | Clean JSON for chosen metrics/range, paginated with a cursor. |
| `get_intraday` | Today's hour-by-hour window from the app's hourly automations (`health-intraday.json`, app 1.4+), replaced each run. |
| `query_health_data` | Natural-language convenience: *"average HRV last month"* routed to structured results. |
| `list_events` | Logged context events (medication, habit, visit, life, shift, episode, travel) with type/tag/date filters. |
| `get_profile` | Opted-in context fields (conditions, medications, goals, allergies, notes) plus `presentFields`. Absent fields were withheld, never "none". |
| `get_workouts` | Workouts by activity/date with pagination; includes heart rate, running dynamics, cycling power, intervals and `hasRoute` when exported. |
| `get_sleep_sessions` | Clustered sleep sessions attributed to the waking day; split nights returned as-is. |
| `get_cycle_context` | Day-in-cycle and coarse phase derived from logged period starts. Never predictive. |
| `correlate_metrics` | Pearson correlation between two metrics with a 0..3 day lag. Association, not causation, always stated. |
| `resolve_metric` | Canonical name and unit for any spelling (`steps`, `StepCount`, `Body Weight`, `hrv`), unit variants with exact formulas, an optional `{value, unit}` conversion, and whether the export holds it. Ambiguous words come back with candidates, never guessed. The data tools accept the same aliases and report `resolvedFrom`. |

**Coverage:** 190 Apple Health metrics across activity, heart, HRV, mobility, respiratory, body, sleep, hearing, and nutrition, plus workouts. Data answers carry honest `coverage` blocks, and single-metric answers list logged events inside the window as `segmentBoundaries` so an average across a medication start or life change cannot masquerade as one regime.

### Data files

The daily cache (`.health-cache.json`) and workouts cache are joined by optional context files, all read-only and all optional: `health-events.json` (the logging surface), `health-profile.json` (opt-in context), `health-sessions.json` (sleep sessions), `health-cycles.json` (observed cycle starts), `health-days.json` (timezone change log). An absent file is reported as `available:false` with a note, never as "no data". Formats: [docs/SCHEMA-CONTRACTS.md](docs/SCHEMA-CONTRACTS.md).

Two patterns worth knowing: [query a parent's Apple Health from your own AI](docs/caregiver-setup.md) (consent-first, the parent's phone is the authority) and [logging data into Apple Health via Shortcuts](docs/shortcuts-write-bridge.md) (the server and app stay strictly read-only).

### MCP prompts

The server ships 22 prompts over `prompts/list` / `prompts/get`: daily brief, weekly review, doctor visit prep, what changed since my last visit, sleep quality and regularity, HRV trend, training and race week reviews, zone minutes, n-of-1 experiment, medication before/after, GLP-1 dose-step compare, sobriety milestone, shift block compare, travel-honest monthly review, cycle-aware trend read, caregiver check-in, glucose day summary, long-term activity narrative, data coverage audit, and a profile-aware context bootstrap. Every prompt leads with coverage honesty and never turns data into diagnosis.

### Demo mode

`node server.mjs --demo` (or `HEALTH_DEMO=1`) serves a deterministic synthetic dataset: ~15 metrics over 400 days, 30 workouts with intervals, 8 events, a profile, 60 sleep sessions, cycle starts and a timezone change, anchored to a fixed date with a seeded PRNG. Every answer carries `demo: true` and a `[SYNTHETIC DEMO DATA]` text prefix, so demo output can never pass for a real export.

### CLI

```bash
node server.mjs --doctor            # diagnostics: files, sizes, schema, freshness, pairing
node server.mjs status --max-age 24 # exit 0 if data is fresh, 1 if stale (cron gate)
node server.mjs receive             # standalone LAN receiver (binds 127.0.0.1 by default)
node server.mjs --help
```

---

## Example AI queries

```text
"What has my resting heart rate done over the last 30 days?"
"Compare my deep sleep this week vs last week."
"Is my VO₂ max trending up or down this quarter?"
"Give me a clean JSON export of HRV, RHR and sleep for the last 14 days."
"Correlate my step count with my sleep duration this month."
```

---

## Use cases

- **AI health coach**, let an agent reason over your real HRV, resting heart rate, and sleep to suggest when to push and when to recover, grounded in your actual numbers instead of generic advice.
- **Training-load analysis**, pull workouts, VO₂ max, and heart-rate trends so your agent can flag overreaching, plot fitness progression, and pace a training block.
- **Sleep correlations**, have your agent correlate deep-sleep duration against steps, caffeine, late workouts, or screen time to find what actually moves your sleep quality.
- **Quantified-self dashboards**, feed clean JSON for any metric set and date range straight into a notebook, spreadsheet, or LLM-built dashboard for your own self-tracking.
- **Personal research & experiments**, run n-of-1 experiments (supplement, routine, or protocol changes) and let an agent compare before/after periods across 190 metrics to see what changed.

---

## The app that feeds it

<p align="center">
  <img src="assets/screenshot-dashboard.png" alt="MetricBridge dashboard" width="240" />
  &nbsp;&nbsp;
  <img src="assets/screenshot-metrics.png" alt="190 Apple Health metrics" width="240" />
  &nbsp;&nbsp;
  <img src="assets/screenshot-destinations.png" alt="Export to iCloud, folder, LAN, or webhook" width="240" />
</p>

<p align="center"><sub><a href="https://www.healthexport.dev">MetricBridge</a>, exports your Apple Health to your agent, automatically.</sub></p>

<p align="center"><a href="https://apps.apple.com/app/id6784185201"><b>Download on the App Store →</b></a></p>

---

## Privacy & security

- **Read-only.** The server only reads your exported data, it never touches HealthKit and never writes back.
- **Local-first.** It runs on your machine over stdio. There is **no developer server** in the path.
- **Optional pairing.** Set `PAIRING_SECRET` to the code the iOS app shows (Settings → Agent pairing) to gate access.
- **Encrypted exports (optional).** If you switch on Export encryption in the iOS app, set `HEALTH_EXPORT_PASSPHRASE` (or `HEALTH_EXPORT_PASSPHRASE_FILE`) to the same passphrase and the server decrypts on your machine. See [Encrypted exports](#encrypted-exports).
- **Auditable.** Zero dependencies and a few hundred lines of readable JavaScript, read every line.
- **Signed releases.** Hosted artifacts are minisign-signed and checksummed, see [Verifying releases](#verifying-releases).

---

## Encrypted exports

The iOS app can encrypt what it exports with a passphrase you choose (Settings > Export encryption,
switched on per destination: iCloud Drive, a folder, your server, the local network). Give the server
the same passphrase and every file is decrypted transparently, in memory, on this machine:

```bash
HEALTH_EXPORT_PASSPHRASE='your passphrase' HEALTH_DATA_DIR=... node server.mjs
# or keep it out of your shell history and process list:
HEALTH_EXPORT_PASSPHRASE_FILE=~/.config/metricbridge/passphrase HEALTH_DATA_DIR=... node server.mjs
```

If both are set, `HEALTH_EXPORT_PASSPHRASE` wins; one trailing newline in the file is ignored and an
empty value counts as unset. The `.mcpb` bundle has an optional **Export passphrase** field. Plaintext
exports keep working either way. A missing or wrong passphrase, or a file that fails its integrity
check, is reported as such (`get_mcp_status` says `encrypted: true` plus the reason, `--doctor` prints
an `encryption:` line), never as "no data". The passphrase is never logged or echoed.

The LAN receiver (`HEALTH_LISTEN=1`) decrypts encrypted pushes with the same variable and answers
`422` with a machine `reason` (`passphrase_missing`, `passphrase_mismatch`, `tampered`, `malformed`,
`unsupported_version`, `passphrase_file_unreadable`, `encryption_required`). The pairing token rides
in a plain `http` header on that leg, so set `HEALTH_REQUIRE_ENCRYPTED=1` to refuse plaintext pushes
once the app encrypts that leg. To decrypt one body yourself (a webhook you run, a script):

```bash
HEALTH_EXPORT_PASSPHRASE='...' node envelope.mjs open body.json     # prints the decrypted JSON
```

**Format** (`metricbridge.enc` v1, `envelope.mjs`, `node:crypto` only): a JSON object
`{format, v, alg: "A256GCM", kdf: "PBKDF2-HMAC-SHA256", iter, salt, kcv, nonce, ct}`.
`master = PBKDF2-HMAC-SHA256(NFC(passphrase), salt[16], iter)` (600,000 iterations, the OWASP
figure); an AES-256-GCM key and an 8-byte key-check value come off it with HKDF-SHA256; each message
gets a random 12-byte nonce; every header field is bound in as AAD as the string
`metricbridge.enc|v=1|alg=A256GCM|kdf=PBKDF2-HMAC-SHA256|iter=<n>|salt=<b64>|kcv=<b64>|nonce=<b64>`.
Base64 is canonical with padding. `test/fixtures/` holds envelopes made by the iOS app's Swift encoder
and by this module; `envelope.test.mjs` proves both open and regenerate byte for byte.

**What it protects:** the export at rest in the destination (iCloud Drive, a synced folder, a
webhook host's storage) and the LAN push on the wire, plus integrity of every sealed file. **What it
does not:** an unlocked phone, this computer (it holds the passphrase), metadata (sizes, timing),
rollback or replay of a whole sealed file, files you share by hand from the app, or a weak passphrase
(anyone with the files can guess offline; the app requires at least 8 characters).

---

## Verifying releases

The server artifacts hosted at `healthexport.dev/mcp/` (used by the [setup skill](https://healthexport.dev/SKILL.md)) are **minisign-signed**, and every download is **SHA-256 checksummed**. The signing public key is published **in this repo** (`minisign.pub`) and in `SKILL.md`, **pin it from here, not only from the website**, so a compromise of the website alone cannot swap both an artifact and its key.

```bash
PUBKEY='RWS6TxVWSKUblYkx7Db6ZpmvHALwHpznZpjaED/FlZj+PpxSlel0MxHZ'   # = minisign.pub in this repo
curl -fsSL https://healthexport.dev/mcp/SHA256SUMS         -o SHA256SUMS
curl -fsSL https://healthexport.dev/mcp/SHA256SUMS.minisig -o SHA256SUMS.minisig
minisign -Vm SHA256SUMS -P "$PUBKEY" || { echo "signature INVALID, do not run"; exit 1; }   # fail closed
curl -fsSL https://healthexport.dev/mcp/server.mjs -o server.mjs
shasum -a 256 --ignore-missing -c SHA256SUMS || { echo "checksum mismatch, do not run"; exit 1; }
```

The pinned, checksum-verified download above is the locked-down path. `npx health-export-mcp` instead resolves the latest version published to npm at run time (npm provides its own package integrity). Full security overview: <https://healthexport.dev/security>. Report vulnerabilities to **security@healthexport.dev**.

---

## Requirements

- **Node.js ≥ 18** (`node -v`).
- A folder containing a `.health-cache.json` exported by [MetricBridge](https://www.healthexport.dev), or run `npm test` to generate a sample one.
- An MCP-compatible client (Claude Desktop, Cursor, opencode, OpenClaw, Hermes, VS Code), or any tool that can read the webhook export.

---

## FAQ

**How do I get my Apple Health data into Claude / ChatGPT / my AI agent?**
Install `health-export-mcp`, export your Apple Health data with the [MetricBridge](https://www.healthexport.dev) iOS app (to iCloud, a folder, or your LAN), then add the MCP server to your AI client. Your agent can then query your Apple Health metrics in natural language. (Non-MCP tools like ChatGPT read the app's webhook export instead.)

**Is my health data sent to a server?**
Not to us. The MCP server runs locally and reads only the export files or endpoints you configure, there's no developer server in the path. Where your iOS export is delivered (iCloud, your LAN, a webhook) is entirely your choice.

**Which agents are supported?**
Any MCP client, Claude Desktop, Cursor, opencode, OpenClaw, Hermes, VS Code, natively. ChatGPT, Gemini, Grok, n8n, and Home Assistant consume the same data via webhook.

**Do I need the iOS app?**
The app is the easiest way to get Apple Health data off your iPhone in the format this server reads. You can also point `HEALTH_DATA_DIR` at any folder containing a compatible `.health-cache.json`.

---

## Troubleshooting

- **"No metrics found"**, confirm `HEALTH_DATA_DIR` points at the folder containing `.health-cache.json`, and that the app has exported at least once. Run `get_mcp_status` to see the resolved source and latest date.
- **Server not visible in the client**, use an **absolute** path to `server.mjs`, ensure Node ≥18, and fully restart the client.
- **Locked data error**, the export file is protected until first unlock after reboot; unlock your device once.

---

## Run it locally

```bash
# Node ≥18, no install needed
HEALTH_DATA_DIR=~/Library/Mobile\ Documents/iCloud~ai~healthexport~app/Documents node server.mjs

# integration test, writes a 14-day sample cache and exercises every tool
npm test
```

stdio transport (newline-delimited JSON-RPC 2.0), the universal MCP transport. Optionally set `HEALTH_LISTEN=1` to also accept LAN pushes from the iOS app in the same process (see [`receiver.mjs`](receiver.mjs)).

---

## How it works

The iOS app reads Apple Health (read-only) and writes a compact `.health-cache.json` (plus optional context files) to the destination you choose. This server reads those files and exposes the 16 tools above over MCP. No bridge, no Docker, no database: just files and stdio.

```
Apple Health → MetricBridge (iOS) → .health-cache.json → health-export-mcp → MCP client → you
```

---

## Related projects

Other Apple Health MCP servers in the ecosystem, worth a look depending on your setup:

- **[neiltron/apple-health-mcp](https://github.com/neiltron/apple-health-mcp)**, an MCP server that runs SQL-style queries over an Apple Health export.
- **[the-momentum/apple-health-mcp-server](https://github.com/the-momentum/apple-health-mcp-server)**, an MCP server for analyzing Apple Health data exported from the Health app.
- **[HealthyApps/health-auto-export-mcp-server](https://github.com/HealthyApps/health-auto-export-mcp-server)**, an MCP server for the Health Auto Export app's data.

**How `health-export-mcp` differs:** zero dependencies, clean structured JSON, 190 Apple Health metrics, and the widest agent support (Claude, Cursor, opencode, OpenClaw, Hermes, VS Code natively, plus ChatGPT/Gemini/Grok/n8n/Home Assistant via webhook).

---

## Related

- **Companion iOS app:** [MetricBridge](https://www.healthexport.dev), exports 190 Apple Health metrics to your agent, automatically.
- **Model Context Protocol:** [modelcontextprotocol.io](https://modelcontextprotocol.io)
- **Per-agent setup:** [AGENTS.md](AGENTS.md)

If this helps your setup, a ⭐ makes it easier for others to find.

## License

MIT, see [LICENSE](LICENSE). Contributions welcome.

---

<sub>Apple Health MCP server · export Apple Health to AI · HealthKit MCP server · query Apple Health with Claude / ChatGPT / Cursor · Model Context Protocol health server · Apple Health to LLM · HRV, sleep & heart rate for AI agents.</sub>