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nnishad

health-relay

by nnishad
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Python
Hybrid

health-relay

Self-hosted bridge between your Samsung Watch → Sync2Ra1 phone app and your Hermes AI agent. The app pushes health readings here over your LAN; the data is stored locally (SQLite) and exposed via REST and MCP so your agent can query it.

Galaxy Watch ─▶ Samsung Health ─▶ Sync2Ra1 (phone) ──push──▶ health-relay ──MCP/REST──▶ Hermes

All data stays on your network. Nothing is sent anywhere else.

Quick start (Docker or Podman)

echo "HR_AUTH_TOKEN=<choose-a-secret>" > .env
docker compose up -d          # or: podman compose up -d
curl http://localhost:8790/healthz     # -> {"ok":true}

Data persists in ./data/ledger.db (SQLite, WAL mode).

Run without Docker

python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
HR_AUTH_TOKEN=<secret> ./run.sh

Point the phone app at it

In Sync2Ra1 → Data tab → Relay (Hermes bridge):

Field

Value

Relay URL

http://<this-machine-ip>:8790

Token

same secret as HR_AUTH_TOKEN

Tap Save → Sync now. Readings arrive within seconds.

Connectivity

phone (Sync2Ra1) ──HTTP :8790──▶ health-relay ◀──MCP stdio / HTTP── Hermes
        same LAN · or Tailscale for anywhere-access

Rule

Detail

Direction

Phone → relay (outbound from phone; nothing connects into the phone)

Port

TCP 8790 inbound to the machine running the relay — open it in that host's firewall

Protocol

Plain HTTP + Authorization: Bearer <token>. Keep it LAN-only, or front with a reverse proxy (Caddy/nginx) for TLS

Anywhere-access

Install Tailscale on the box and phone; point the app at the Tailscale IP (http://100.x.y.z:8790) — encrypted, works over mobile data, no ports exposed to the internet

Cadence

App auto-syncs hourly + on app launch + manual Sync now

Offline

Phone buffers everything in local SQLite; on reconnect it pushes the full backlog (oldest first) and re-syncs the last 48 h so Samsung's revisions propagate

Duplicates

Impossible to double-count — every reading has a unique key; replays are ignored server-side

Hermes location

Same machine (MCP runs as a local subprocess reading the SQLite file) or remote (use the REST endpoints instead of MCP)

REST API (bearer auth)

Endpoint

Purpose

GET /healthz

liveness (no auth)

POST /api/v1/health/samples

batch ingest — idempotent, replays are no-ops

GET /api/v1/health/samples?type=&from_ms=&to_ms=&limit=&offset=

raw readings

GET /api/v1/health/daily-summary?date=YYYY-MM-DD&tz=Europe/London

per-metric min/max/avg/count

GET /api/v1/health/trends?type=X&days=N&tz=Europe/London

daily rollups

GET /api/v1/health/status

totals per type

curl -H "Authorization: Bearer <secret>" \
  "http://localhost:8790/api/v1/health/daily-summary?date=$(date +%F)&tz=Europe/London"

Plug into Hermes (MCP)

The MCP server reads the same SQLite file — run it from this repo:

python3 -m venv .venv-mcp
.venv-mcp/bin/pip install fastmcp

Add to your agent's MCP config:

{
  "mcpServers": {
    "health-relay": {
      "command": "<repo-path>/.venv-mcp/bin/python",
      "args": ["<repo-path>/mcp_server.py"],
      "env": { "HR_DATA_DIR": "<repo-path>/data" }
    }
  }
}

Tools your agent gets

Tool

Answers questions like

list_streams()

"what health data do you have?"

get_samples(type, from_ms, to_ms)

"show my heart rate this morning"

daily_summary(date, tz)

"how active was I yesterday?"

sleep_breakdown(nights)

"how did I sleep this week?"

Day boundaries respect your timezone (tz="Europe/London" etc., DST handled).

Recorded streams

Heart rate · SpO₂ · skin temperature · respiration · resting HR · VO₂max · sleep duration/score/stages · steps & floors (hourly + daily) · workouts · activity calories/time/distance · body composition (BIA) · energy score · blood pressure · glucose · hydration · meals.

Configuration

Env var

Default

HR_AUTH_TOKEN

(empty = auth off)

set this in production

HR_PORT

8790

HR_HOST

0.0.0.0

keep on trusted LAN

HR_DATA_DIR

~/health-relay-data

SQLite lives here

Tests

.venv/bin/python -m pytest tests/ -q

This server cannot be installed

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maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

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