health4.ai — Apple Health × AI

Ask your AI about your sleep, HRV, recovery, and fitness — in plain language.
Free iOS app · Your own database · Works with any MCP client

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What it does

iPhone HealthKit → Your Postgres database → MCP server → Any AI

Apple Health holds years of your biometric data — sleep stages, HRV, heart rate, workouts, VO₂ max, and 150+ other metrics. health4.ai makes all of it queryable from Claude, ChatGPT, Cursor, Ollama, or any MCP-compatible client via 8 purpose-built tools.

You control the data. It syncs to a Postgres database you configure — Supabase, Neon, or a local Docker container. health4.ai never stores or has access to your health data.

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Why it exists

Problem	health4.ai fix
Apple has no HealthKit server API — all access requires an on-device app	Native iOS app with HKObserverQuery + BGTaskScheduler background sync
Health Auto Export only works on the same WiFi	Your data lands in Postgres — queryable from any AI, anywhere
The claude.ai Apple Health connector doesn't reach Claude Code CLI or Cursor	Standard MCP (stdio) — one config block works everywhere
Most solutions require a managed cloud service	Bring your own Postgres: Supabase, Neon, or fully local

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Demo

Demo video coming. Here's what a typical conversation looks like:

You:     How was my recovery this week? Anything standing out?

Claude:  Your recovery this week was mixed but trending positive.
         • HRV averaged 58ms (Tue–Thu strong at 64–68ms; Monday low at 44ms after Saturday's long run)
         • Sleep averaged 7h 12m — Wednesday and Thursday were your best nights (7h 40m+)
         • Resting HR dropped from 54bpm Monday to 49bpm Friday — a good sign
         Recommendation: today looks like a solid day for a moderate-intensity session.

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Quick start

Choose your Postgres backend first:

Supabase (free tier available)

# 1. Create a project at supabase.com
# 2. Run the schema
psql "$DATABASE_URL" < web/public/schema.sql
# or use the Supabase dashboard SQL editor

Neon (serverless Postgres)

# 1. Create a project at neon.tech
# 2. Run the schema
psql "$DATABASE_URL" < web/public/schema.sql

Local Docker

docker run -d \
  --name health4ai-postgres \
  -e POSTGRES_PASSWORD=yourpassword \
  -p 5432:5432 \
  postgres:16
psql "postgresql://postgres:yourpassword@localhost:5432/postgres" \
  < web/public/schema.sql

Then set up the MCP server:

git clone https://github.com/jefflitt1/health4ai.git
cd health4ai

cp mcp-server/.env.example mcp-server/.env

Edit mcp-server/.env:

DATABASE_URL=postgresql://...    # your Postgres connection string
HEALTHKIT_USER_ID=your_user_id   # any string to identify your data

Add to your AI client:

Claude Code / Claude Desktop

{
  "mcpServers": {
    "health4ai": {
      "command": "python",
      "args": ["/path/to/health4ai/mcp-server/main.py"],
      "env": {
        "DATABASE_URL": "postgresql://...",
        "HEALTHKIT_USER_ID": "your_user_id"
      }
    }
  }
}

Cursor

Same block → ~/.cursor/mcp.json

Ollama (fully local — no data leaves your machine)

Pair with mcphost or mcp-client-for-ollama:

mcphost --model ollama/llama3.2 \
  --mcp-server "health4ai:python /path/to/health4ai/mcp-server/main.py"

Your health data and the model both stay on your hardware — nothing leaves your machine.

Install the iOS app: TestFlight link coming at App Store launch. Sign in with your database credentials and tap Start Sync.

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MCP tools

Tool	What it answers
get_health_summary	Overview of key metrics for the past N days
get_sleep	Per-night sleep breakdown with REM, Deep, Core stages
get_hrv_trend	Daily HRV (SDNN) with rolling comparison and trend
get_daily_snapshot	Everything recorded for a specific date
get_workouts	Recent workouts with type, duration, distance, calories
query_metric	Raw time-series for any HealthKit metric type
get_long_term_trend	Monthly aggregates over years (raw + summary tiers)
get_coaching_brief	Recovery status, sleep quality, training load, fitness markers
search_records	Find days where a metric crossed a threshold
get_metric_stats	Personal baseline: min/max/mean/percentiles
compare_periods	Compare a metric between two date ranges

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Architecture

┌─────────────────────────────────────────────────────────────┐
│  iPhone                                                      │
│  HKObserverQuery + BGTaskScheduler                          │
│  → continuous background sync                               │
└──────────────────────────┬──────────────────────────────────┘
                           │ HTTPS
                           ▼
┌─────────────────────────────────────────────────────────────┐
│  Your Postgres database (Supabase / Neon / local Docker)    │
│  healthkit_metrics · healthkit_daily_summaries              │
│  v_healthkit_daily_quantity (unified view)                  │
└──────────────────────────┬──────────────────────────────────┘
                           │ SQL (service-role key, server-side only)
                           ▼
┌─────────────────────────────────────────────────────────────┐
│  FastMCP server  (mcp-server/main.py)                       │
│  11 tools · stdio transport                                  │
└──────────────────────────┬──────────────────────────────────┘
                           │ MCP
                           ▼
              Claude · ChatGPT · Cursor · Ollama · any client

Data tiers: queries within the last 30 days return raw samples; older data transparently switches to pre-aggregated daily summaries — so long-term trend queries stay fast regardless of data volume.

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Repo structure

health4ai/
├── ios/                         # Swift/SwiftUI iOS app (iOS 17+)
│   └── Health4AI/               # HealthKit sync engine, auth, settings
├── mcp-server/
│   ├── main.py                  # FastMCP server entry point
│   ├── tools.py                 # 11 tool implementations
│   └── .env.example             # Required environment variables
├── web/
│   ├── public/schema.sql        # Portable Postgres schema (all backends)
│   └── src/                     # Astro marketing site
├── scripts/
│   ├── import_health_export.py  # One-time XML backfill from Apple Health export
│   └── summarize_historical.py  # Backfill daily summaries table
└── docs/
    └── SETUP.md                 # Detailed setup guide

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Privacy

Your health data goes directly from your iPhone to your Postgres database. health4.ai never receives, stores, or has access to it. The MCP server runs locally with your own credentials — your data never touches our infrastructure.

See the Privacy Policy for full details.

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Contributing

MIT licensed. PRs welcome.

Good first areas: additional metric aggregations, multi-user support with JWT/RLS, Android, and more MCP client integration guides.

License

MIT — see LICENSE.