Codync
免费开源的 1:1 Grok Bot 与 Muse 替代方案。可在 iPhone、Mac 或 Linux 桌面上将 Claude 代码、Codex、Cursor 以及 40 多个编码代理作为持久机器人使用。支持群组聊天、线程、应用。
AI 翻译
Open-source Apple Health MCP server for the MetricBridge iOS app: query 194 HealthKit metrics from Claude, ChatGPT, Cursor, OpenClaw, Hermes and any AI agent. Zero-dependency, local-first, read-only.
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查看完整 README ↗An MCP server for your own Apple Health data. 194 metrics, 21 tools (19 read-only, plus two that log events to their own file) and 23 prompts over local stdio, with zero dependencies, no account and no server of ours in the path. Your agent gets JSON with units, date ranges and coverage, and answers from your numbers.
Docs and per-client config: healthexport.dev/mcp · agents can run the setup from SKILL.md · privacy: the server reads a local file and makes no network requests, so your health data never reaches us or a cloud AI through it.
claude mcp add health-export -- npx -y health-export-mcp
On a Mac that is the whole install: since 1.7.3 the server finds the MetricBridge app's iCloud Drive folder by itself. On Windows or Linux, or for an export in another folder, add --env "HEALTH_DATA_DIR=/path/to/folder" before the --. Needs Node.js 18 or later. Claude Desktop: open health-export.mcpb instead (no JSON, no Node on your PATH). Cursor, VS Code, opencode, OpenClaw, Hermes: AGENTS.md.
Then ask "Use health-export: how did my HRV this week compare with last week?" The agent calls get_trends and gets numbers that carry their own provenance: unit, exact date ranges, whether each window was complete, and how much history the export holds. This is the real output on 1.7.3 (from the built-in --demo dataset, which is synthetic so it can be published; a real export answers with the same fields and without the watermark):
[SYNTHETIC DEMO DATA] {"metric":"heart_rate_variability","unit":"ms","window":7,"recent":50.859,"prior":51.306,
"change":-0.447,"changePercent":-0.871,"direction":"flat","recentRange":{"from":"2026-08-12","to":"2026-08-18"},
"recentDays":7,"priorDays":7,"windowSatisfied":true,"coverage":{"firstDate":"2025-07-15","lastDate":"2026-08-18","days":400}}
No iPhone yet? claude mcp add health-export-demo -- npx -y health-export-mcp --demo serves that watermarked synthetic dataset, so you can try every tool in 30 seconds before installing anything on a phone.
.health-cache.json to iCloud Drive (or a folder, or your LAN). The app has a 7-day free trial, then one purchase ($24.99), no subscription. This server is MIT and free..mcpb (Claude Desktop), or the block for your client in AGENTS.md.npx -y health-export-mcp --doctor prints the folder it chose and why, each file's age, and freshness. iCloud can take a few minutes to bring a new export to the Mac.It's an MCP server that turns your Apple Health export into tools your AI agent can query in natural language: HRV, sleep, resting heart rate, steps, workouts, VO₂ max and 180+ more.
health-export-ai in serverInfo, and the npm package and repository names are unchanged.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_statusreportslastDataDateand the intradaylastWrite, which is the quickest way to tell "still syncing" from "never arrived".
Try it with no iPhone needed:
npx -y health-export-mcp --demo(ornode server.mjs --demoin a clone) serves a deterministic synthetic dataset (400 days, workouts, events, sleep sessions) with every answer watermarked as synthetic. Or runnpm testto write a sample cache and exercise every tool.
The companion iOS app MetricBridge 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.
Fastest, one command (Claude Code):
claude mcp add health-export -- npx -y health-export-mcp
# Windows, Linux, or an export outside iCloud Drive:
claude mcp add health-export --env "HEALTH_DATA_DIR=/path/to/folder" -- npx -y health-export-mcp
Everything before -- is an option for claude mcp add, everything after it is the command that starts the server. On a Mac the server reads the app's iCloud Drive folder when HEALTH_DATA_DIR is unset (1.7.3+); if you set it to that folder by hand, double-quote it (the folder name contains a space) and use $HOME, because a quoted ~ is not expanded by the shell. Add --scope user to make the server available in every project (the default scope is the current project only). Check it with claude mcp list.
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json), and any client that takes an mcpServers block:
{
"mcpServers": {
"health-export": {
"command": "npx",
"args": ["-y", "health-export-mcp"]
}
}
}
Off a Mac, or for another folder, add
"env": { "HEALTH_DATA_DIR": "/path/to/folder" }to the entry (a leading~is expanded by the server).npx -yfetches the published package at run time without an install prompt (npm verifies package integrity), so it runs anywhere with no clone or absolute path. The server expands a leading~inHEALTH_DATA_DIRitself, so the JSON form can keep it. Prefer to pin a vetted local checkout instead? Use"command": "node", "args": ["REPLACE_WITH_ABSOLUTE_PATH/server.mjs"], get the path withnode -e "console.log(process.cwd()+'/server.mjs')"inside the repo. Or skip JSON entirely, draghealth-export.mcpbinto Claude Desktop → Settings → Extensions.
Auto-configure from a clone:
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
Cursor / VS Code: node gen-deeplinks.mjs prints one-click install links.
opencode / OpenClaw / Hermes: see AGENTS.md for the exact block, same shape, one per client.
Restart the client and try:
"Use health-export: what's my average HRV this week vs last week?"
| Client / Agent | Integration | How |
|---|---|---|
| Claude Code | Native MCP | claude mcp add ... -- npx -y health-export-mcp |
| 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 |
*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.
Full reference with request/response examples: healthexport.dev/mcp.
| 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 judged on the core files (daily cache, sleep sessions) 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. state: "stale_copy" (with a stale_copy list) when the phone's .health-manifest.json or iCloud says this Mac holds an older copy of a core file than the phone wrote. 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). Blood pressure at day granularity also lists the individual readings (health-readings.json). |
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 | The hour-by-hour window from the app's hourly automations (health-intraday.json, app 1.4+): yesterday and today, replaced each run, with each hour's Min/Max for discrete metrics when the app writes them. |
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, from the app and from , each labelled or . |
Coverage: 194 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.
The daily cache (.health-cache.json) and workouts cache are joined by optional context files, 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), health-readings.json (individual blood pressure readings), health-check-ins.json (morning check-ins, opt-in), health-strength.json (the strength log, when its export is switched on), health-tags.json (logged tags with supplements marked, opt-in in the app) and .health-manifest.json (what the phone last wrote, for the stale-copy check). The server reads all of them and writes only health-events-agent.json (events logged with add_event). An absent file is reported as available:false with a note, never as "no data". Formats: docs/SCHEMA-CONTRACTS.md.
Two patterns worth knowing: query a parent's Apple Health from your own AI (consent-first, the parent's phone is the authority) and logging data into Apple Health via Shortcuts (the server never writes to Apple Health).
The server ships 23 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, a nutrition week summary, and a profile-aware context bootstrap. Every prompt leads with coverage honesty and never turns data into diagnosis.
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, a timezone change and 30 days of tags, 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.
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 or a stale iCloud copy (cron gate)
node server.mjs receive # standalone LAN receiver (binds 127.0.0.1 by default)
node server.mjs --help
"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."
This server reads a file the MetricBridge iOS app writes on the user's own device, with no central health-data processor in the path. The same app can POST signed JSON (Standard Webhooks v1, published JSON Schemas) straight to your endpoint, so your users bring their own Apple Health to your product without an SDK in your app and without any vendor server holding the data. The offer, flat pricing and boundaries: healthexport.dev/platforms. The integration guide and the zero-dependency conformance kit: healthexport.dev/docs/platforms. Wellness-scoped and end-user-directed; no clinical or HIPAA work.
The one non-health thing the server reads from the export is _meta.license, a marker the app writes
with exactly two shapes: {"state": "trial", "daysRemaining": N} or {"state": "unlocked"}. A fresh
export from a trial adds one sentence to get_freshness naming when the trial ends; an unlocked export
adds nothing. No network call is involved and nothing is sent anywhere.
health-events-agent.json, the events an agent logs with add_event / remove_event; it never modifies a file the app writes. Both tools are refused in demo mode and on a read-only folder, and the file is sealed like the rest of an encrypted export.PAIRING_SECRET to the code the iOS app shows (Settings → Agent pairing) to gate access.HEALTH_EXPORT_PASSPHRASE (or HEALTH_EXPORT_PASSPHRASE_FILE) to the same passphrase and the server decrypts on your machine. See Encrypted exports.get_mcp_status always includes one static link to the companion app's website (and its App Store page), so the bridge is attributable back to install. Both links carry fixed campaign labels (utm_source=mcp, utm_medium=agent-tool, utm_campaign=mcp-unlock; ct=mcpserver, ppid=…) that are identical for every user and contain nothing about you or your data; they only count if you choose to open one.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:
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):
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).
The server artifacts hosted at healthexport.dev/mcp/ (used by the setup skill) 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.
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 -y health-export-mcp instead resolves the latest version published to npm at run time (npm provides its own package integrity). GitHub releases carry a SHA256SUMS file and a CycloneDX SBOM (*.cdx.json); a SHA256SUMS.minisig made with the same key is attached once the maintainer has signed that release locally, so check for it before relying on it. Full policy, including npm provenance and how to report a vulnerability privately: SECURITY.md. Security overview: https://healthexport.dev/security.
node -v)..health-cache.json exported by MetricBridge, or run npm test to generate a sample one.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 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?
For your own data, yes: the server reads the file the MetricBridge app writes and never talks to HealthKit itself. To evaluate first, --demo serves a watermarked synthetic dataset with no app and no iPhone.
npx -y health-export-mcp --doctor. It prints the folder the server chose and why (HEALTH_DATA_DIR, the iCloud default on a Mac, or the current directory) and whether .health-cache.json is there. Confirm the app has exported at least once; get_mcp_status shows the same source and the latest date.npx -y health-export-mcp --doctor in a terminal. If it works there, the client can't find npx (common for Claude Desktop with Node from nvm or Homebrew): use the .mcpb, or set "command" to the full path from which npx. Then fully quit and reopen the client.get_freshness reports the export as stale and links the unlock page; once the app is unlocked, exports resume with no change on this side.state: "stale_copy": this Mac's iCloud Drive has an older copy of the export than the phone wrote. Wait a few minutes, or open the MetricBridge folder in iCloud Drive in Finder and choose Download Now on the file (Remove Download drops only this Mac's local copy, and it downloads again). --doctor lists each stale copy.# 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).
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 21 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
Other Apple Health MCP servers in the ecosystem, worth a look depending on your setup:
How health-export-mcp differs: the iPhone app keeps the export current in the background, so there's no manual export.xml and no re-import; the server has zero dependencies and needs no Docker, database or Mac app; every answer carries its units, date range and coverage; and it never writes to Apple Health: its only write is the events file your agent logs to.
If this helps your setup, a ⭐ makes it easier for others to find.
MIT, see LICENSE. Contributions welcome.
add_eventsource: "app""agent"add_event | Log an event the user states (a medication start, a trip) into health-events-agent.json, the one file this server writes. Idempotent by clientEventId. |
remove_event | Remove an event logged with add_event. Events logged in the iOS app are edited there. |
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 separate sessions, duplicate copies of one night collapsed (collapsedDuplicates). |
get_strength_log | The strength log typed into the iOS app (health-strength.json, opt-in, off by default): each session with every set as entered, volumeKg, workingSets, an Epley bestEstimateKg per exercise, all-time records, and the user's saved routines. Filter by exercise, start, end. Missing file → available:false. |
get_check_ins | Morning check-ins the user chose to share (health-check-ins.json, off by default in the app): self-rated feeling 1 to 5, note, intention and whether it happened, plus a summary. A self-rating, not a measurement. |
get_cycle_context | Day-in-cycle and coarse phase derived from logged period starts. Never predictive. |
list_tags | Tags logged in the app (health-tags.json, opt-in there and off by default): lifestyle tags and supplements by name, never an amount. {kind: all, supplement or lifestyle, start, end}; one row per tag plus the names per day. |
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. When the export carries per-source attribution (app builds that write src/by on daily points and a health-sources.json, cache schema minor 2), the answer adds a sources block naming the devices that fed the export, which one won each metric and the priority rules, and sourceMerge reports disagreement as visible; older exports report it as not available. |