Owntracks

OwnTracks Location Receiver

Give your AI agent GPS awareness. Zero dependencies, one Node.js file.

Architecture

OwnTracks app → (HTTPS via Cloudflare Tunnel) → server.mjs → data/
                                                         ├── current-location.json
                                                         └── location-log.jsonl

Setup

1. Start the receiver

AUTH_USER=yi AUTH_SECRET=$(openssl rand -base64 24) node scripts/server.mjs
# Default port 8073. Override with PORT=9090

Without AUTH_SECRET, the server runs open (fine for localhost, not for public URLs).

2. Expose via tunnel (if behind NAT)

Pick one:

Option A: ngrok (quick start)

ngrok http 8073
# Copy the https://xxx.ngrok-free.app URL to OwnTracks

Option B: Cloudflare Tunnel (permanent)

# One-time setup
brew install cloudflared
cloudflared tunnel login
cloudflared tunnel create owntracks
cloudflared tunnel route dns owntracks gps.yourdomain.com

# Create ~/.cloudflared/config.yml:
# tunnel: <tunnel-id>
# credentials-file: ~/.cloudflared/<tunnel-id>.json
# ingress:
#   - hostname: gps.yourdomain.com
#     service: http://localhost:8073
#   - service: http_status:404

# Run (use --protocol http2 in China where QUIC is blocked)
cloudflared tunnel run owntracks

Tip: set up as a launchd service for auto-start on boot.

3. Configure OwnTracks app

• Mode: HTTP
• URL: Your tunnel URL (ngrok URL or https://gps.yourdomain.com/)
• Authentication: Username + password (matching AUTH_USER / AUTH_SECRET)
• Monitoring: Significant (battery-friendly) or Move (precise tracking)

⚠️ OwnTracks may add trailing spaces when pasting passwords. The server trims automatically.

Named Places

Copy and edit the example:

cp scripts/places.example.json places.json
# Edit places.json with your locations

Format:

{
  "places": [
    { "name": "home", "label": "Home", "lat": 37.775, "lon": -122.419, "radius": 200 },
    { "name": "office", "label": "Office", "lat": 37.790, "lon": -122.389, "radius": 300 }
  ]
}

With places configured, queries return semantic locations ("At 家") instead of raw coordinates.

Querying Location

# Current location + nearest place
node scripts/query.mjs

# JSON output (for programmatic use)
node scripts/query.mjs --json

# Last N locations
node scripts/query.mjs --history 5

# Locations from a specific date
node scripts/query.mjs --at 2026-03-10

# List configured places
node scripts/query.mjs --places

Direct file access

cat data/current-location.json          # latest location
tail -5 data/location-log.jsonl         # recent history

Location fields

lat, lon, alt, acc (meters), vel (km/h), batt (%), conn (w=wifi, m=mobile), tid, tst (epoch), timestamp (ISO), receivedAt (ISO).

Use Cases for Agents

• Context awareness: "You're still at the office at 11pm — time to head home?"
• Proactive help: Detect arrival at airport → check flight status
• Smart home: Detect "at home" → trigger automations
• Daily journaling: Log places visited with timestamps
• Safety: Alert if no location update for extended period

Nearby Search (AMap/高德)

Requires AMAP_API_KEY env var. Get a free key at https://lbs.amap.com

Coordinate System (China users)

AMap requires GCJ-02 coordinates. iOS CoreLocation returns WGS-84 (the GPS standard), and the nearby.mjs script includes a built-in WGS-84 → GCJ-02 converter (default: COORD_SYSTEM=wgs84). If your device already provides GCJ-02, set COORD_SYSTEM=gcj02 to skip conversion:

# iOS / standard GPS devices (default, auto-converts WGS→GCJ)
node scripts/nearby.mjs "咖啡"

# If your device already reports GCJ-02
COORD_SYSTEM=gcj02 node scripts/nearby.mjs "咖啡"

# Auto-uses current GPS location
node scripts/nearby.mjs "咖啡"

# Custom radius and explicit coordinates
node scripts/nearby.mjs "餐厅" --radius 1000 --lat 37.775 --lng -122.419

# JSON output for programmatic use
node scripts/nearby.mjs "药店" --json

# Limit results
node scripts/nearby.mjs "便利店" --limit 5

Combines with GPS: if OwnTracks is running, nearby search auto-detects your location. No need to pass coordinates.

Use cases: restaurants, cafes, pharmacies, hospitals, transit, gyms — anything in AMap's POI database (excellent coverage in China).

Files

• scripts/server.mjs — HTTP receiver (zero deps)
• scripts/query.mjs — CLI query tool (zero deps)
• scripts/nearby.mjs — AMap nearby POI search (zero deps, needs AMAP_API_KEY)
• scripts/gps-inject.sh — Injects GPS status into HEARTBEAT.md (for agent context)
• scripts/places.example.json — Example places config
• places.json — Your places config (create from example, gitignored)
• data/ — Location data (created automatically, gitignored)

Heartbeat Integration (Agent GPS Awareness)

The key challenge: an agent's heartbeat reads HEARTBEAT.md, but may skip instructions inside it. The solution is code-level injection — a shell script writes GPS status directly into HEARTBEAT.md so the data is already in the agent's system prompt.

How it works

launchd (every 2 min) → gps-inject.sh → reads GPS data → writes to HEARTBEAT.md header
                                                          ↓
                                         Agent heartbeat reads HEARTBEAT.md
                                         GPS data is already in system prompt
                                         Agent can't "forget" to check GPS

Setup

1. Copy and edit scripts/gps-inject.sh:

   • Set GPS_FILE to your data/current-location.json path
   • Set HEARTBEAT to your agent's HEARTBEAT.md path
   • Create a known-places.json with your named locations (see format below)

2. Create a launchd plist (macOS) or cron entry:

<!-- ~/Library/LaunchAgents/com.agent.gps-inject.plist -->
<plist version="1.0">
<dict>
    <key>Label</key><string>com.agent.gps-inject</string>
    <key>ProgramArguments</key>
    <array>
        <string>/bin/bash</string>
        <string>/path/to/scripts/gps-inject.sh</string>
    </array>
    <key>StartInterval</key><integer>120</integer>
    <key>RunAtLoad</key><true/>
</dict>
</plist>

launchctl bootstrap gui/$(id -u) ~/Library/LaunchAgents/com.agent.gps-inject.plist

3. Your HEARTBEAT.md will automatically show:

<!-- GPS_START -->
> 📍 User at Home | Updated 09:53 (1 min ago) | 🔋85% WiFi | Accuracy 7m
<!-- GPS_END -->

Known places format

[
  {"name": "Home", "lat": 40.033, "lon": 116.417, "radius": 0.003},
  {"name": "Office", "lat": 40.052, "lon": 116.294, "radius": 0.003}
]

Use coordinates from your actual GPS data (same coordinate system). For unknown locations, the script falls back to OSM Nominatim reverse geocoding (WGS-84, free, no API key).

Why this pattern matters

Text-level instructions ("check GPS every heartbeat") are unreliable — agents read them but may not execute. Code-level injection bypasses the agent's decision-making entirely: the data is in the prompt whether the agent "remembers" to check or not. This is a general pattern: if an agent must see something, inject it into context; don't ask the agent to go look.