GET /v1/weather/{location}

Parameters:
  location   string   required   Lat,lon / city / ZIP / airport code
  hours      int      48         Hours of hourly forecast (max 384)
  days       int      7          Days of daily forecast (max 16)
  models     string   "best"     "best", "gfs", "ecmwf", "hrrr", "all"
  units      string   "metric"   "metric", "imperial", "si"
  fields     string   "standard" "standard", "all", or comma-separated

{
  "location": {
    "lat": 40.7128, "lon": -74.006,
    "name": "New York, NY",
    "elevation_m": 10,
    "timezone": "America/New_York"
  },
  "current": {
    "time": "2026-03-14T15:00:00Z",
    "temperature_c": 12.3,
    "feels_like_c": 10.1,
    "humidity_pct": 65,
    "wind_speed_ms": 4.2,
    "wind_direction_deg": 270,
    "cloud_cover_pct": 40,
    "solar_irradiance_wm2": 310,
    "uv_index": 4,
    "weather_description": "Partly cloudy",
    "source": "nws_observation"
  },
  "hourly": [
    {
      "time": "2026-03-14T16:00:00Z",
      "temperature_c": 12.1,
      "wind_speed_ms": 4.5,
      "precipitation_probability_pct": 10,
      "solar_irradiance_wm2": 280,
      "source": "model_blend_gfs_ecmwf"
    }
  ],
  "daily": [
    {
      "date": "2026-03-15",
      "temperature_max_c": 14.2,
      "temperature_min_c": 5.8,
      "precipitation_sum_mm": 2.1,
      "heating_degree_days": 12.1,
      "cooling_degree_days": 0,
      "source": "model_blend_gfs_ecmwf"
    }
  ],
  "meta": {
    "credits_used": 1,
    "models_used": ["gfs", "ecmwf_ifs"],
    "generated_at": "2026-03-14T15:02:00Z"
  }
}

# All requests require a Bearer token
curl "https://api.qanto.com/v1/weather/london" \
  -H "Authorization: Bearer qnt_live_YOUR_API_KEY"

# Or for AI agents via x402 (no API key needed):
# Agent sends request → receives HTTP 402 → pays USDC → retries with payment proof

import requests

response = requests.get(
    "https://api.qanto.com/v1/weather/40.71,-74.01",
    headers={"Authorization": "Bearer qnt_live_abc123"}
)

data = response.json()
print(f"Temperature: {data['current']['temperature_c']}°C")
print(f"Wind: {data['current']['wind_speed_ms']} m/s")

# Intelligence endpoint
impact = requests.get(
    "https://api.qanto.com/v1/intelligence/impact",
    params={"location": "51.5,-0.12", "operation": "wind_farm"},
    headers={"Authorization": "Bearer qnt_live_abc123"}
)
print(f"Impact Score: {impact.json()['impact_score']}/10")

# Create a custom weather alert
curl -X POST "https://api.qanto.com/v1/alerts/rules" \
  -H "Authorization: Bearer qnt_live_abc123" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "North Sea Wind Drop",
    "location": { "lat": 55.0, "lon": 3.0 },
    "condition": "wind_speed_ms < 5",
    "forecast_window_hours": 48,
    "notify": {
      "webhook": "https://your-system.com/weather-hook",
      "slack": "#energy-desk"
    }
  }'

# AI agent requests weather data
GET /v1/weather/london HTTP/1.1

# Server responds with payment instructions
→ 402 Payment Required
  X-Payment-Amount: 0.005
  X-Payment-Currency: USDC
  X-Payment-Address: 0x...
  X-Payment-Network: base

# Agent signs USDC payment, retries with proof
GET /v1/weather/london HTTP/1.1
  Payment-Signature: 0x...

# Server verifies payment, returns data
→ 200 OK
  { "current": { "temperature_c": 12.3, ... } }