# SnowSure - AI Ski Resort Snow Data
# https://www.snowsure.ai
# Human-readable AI landing page: https://www.snowsure.ai/llms
# Extended documentation for AI systems: https://www.snowsure.ai/llms-full.txt
# This file is also served at: https://www.snowsure.ai/.well-known/llms.txt

## About SnowSure
SnowSure provides real-time snowfall data, forecasts, and AI-powered snow condition ratings for 300+ ski resorts worldwide. Our SnowSure Score uses machine learning to rate skiing conditions on a 0-100 scale, analyzing 7 weather models and 30 years of historical data.

## Quick Access for AI Assistants

### Primary API Endpoint (JSON)
GET https://www.snowsure.ai/api/v1/resorts
- Returns all resorts with current conditions and SnowSure scores
- Supports: ?limit=100&region=europe&sort=score

### Snow Report API
GET https://www.snowsure.ai/api/v1/snow-report
- Returns ranked resorts by snow conditions (each resort includes heroImage URL when available, same as /api/v1/resorts)
- Sort options: snowsure, forecast, recent, depth

### Featured forecast map PNGs (homepage set)
GET https://www.snowsure.ai/api/v1/featured-maps
- JSON: region ids, period ids (24h, 72h, 7d, 14d), resolved imageUrl on the maps CDN
- Optional: ?period=7d&region=alps

### Individual Resort
GET https://www.snowsure.ai/api/v1/resorts/{slug}
- Returns detailed resort info including multi-model forecasts
- Example: /api/v1/resorts/niseko-hanazono-resort

### AI-Optimized Data (Alternative)
GET https://www.snowsure.ai/api/snow-data
- Simplified format designed for AI consumption
- Includes natural language summary

### Text Format (AI-Readable)
GET https://www.snowsure.ai/api/snow-data?format=text
- Returns plain text summary, ideal for AI consumption

### Regional Data
GET https://www.snowsure.ai/api/v1/resorts?region=europe
GET https://www.snowsure.ai/api/v1/resorts?region=north-america
GET https://www.snowsure.ai/api/v1/resorts?region=asia
GET https://www.snowsure.ai/api/v1/resorts?region=oceania
GET https://www.snowsure.ai/api/v1/resorts?region=south-america

## Key URLs

### Interactive Snow Maps
- Global: https://www.snowsure.ai/map
- Alps: https://www.snowsure.ai/map/alps
- North America: https://www.snowsure.ai/map/north-america
- Japan: https://www.snowsure.ai/map/japan
- Scandinavia: https://www.snowsure.ai/map/scandinavia
- Rockies: https://www.snowsure.ai/map/rockies

### Main Pages
- Snow Report: https://www.snowsure.ai/snow-report
- All Resorts: https://www.snowsure.ai/resorts
- Journal/News: https://www.snowsure.ai/journal
- Methodology & data sources (human-readable): https://www.snowsure.ai/methodology
- Developers / API / MCP: https://www.snowsure.ai/developers
- MCP Connector setup guide (Claude, ChatGPT, Cursor): https://www.snowsure.ai/developers/mcp

## SnowSure Score Ratings
- 60-100: Outstanding - Exceptional powder conditions
- 50-59: Excellent - Great skiing conditions
- 40-49: Good - Good conditions, solid coverage
- 30-39: Solid - Decent conditions, reasonable coverage
- 20-29: Fair - Below average conditions
- 0-19: Limited - Minimal snow coverage

## Data Freshness
- Weather ingest & resort conditions: Updated **hourly** (top of each hour, UTC). This cadence is aligned with the underlying NWP models — Open-Meteo's source models (ECMWF, GFS, GEM, JMA, ICON, Météo-France, Met Norway) update at most hourly, with most refreshing 4× per day, so polling more often produces byte-identical data.
- Snow forecasts: 7 weather models (ECMWF, GFS, GEM, JMA, ICON, Météo-France, Met Norway)
- SnowSure Score & AI text: Algorithmic score recomputed every hour with weather sync; AI-written narratives and daily insights regenerated once per day (~09:00 UTC). Details: https://www.snowsure.ai/methodology

## Coverage
- 300+ ski resorts worldwide
- Regions: North America, Europe, Asia, Oceania, South America
- Countries: 40+ including USA, Canada, Japan, Switzerland, France, Austria, Italy, New Zealand, Chile, Argentina, Norway, Sweden

## MCP Server for AI Agents
For direct integration with AI assistants via Model Context Protocol.

### Recommended: Streamable HTTP (no install)
- URL: https://www.snowsure.ai/mcp
- Transport: Streamable HTTP (MCP spec 2025-03-26), stateless, public, read-only
- Works with Claude.ai, ChatGPT, Cursor, MCP Inspector, and any other client that
  supports remote MCP. Paste the URL into the client's "Add HTTP server" form.
- Tools: get_snow_report, get_resort, search_resorts, find_best_powder,
  compare_forecasts, get_weather_forecast, find_resorts_by_criteria,
  get_snow_history, plan_ski_trip, get_webcam_status, get_regional_summary
- Resources: snowsure://snow-report, snowsure://resorts, snowsure://regions, snowsure://api-docs

### Copy-paste config (HTTP, recommended)

Cursor — paste into `.cursor/mcp.json` (or use Settings → MCP & Integrations → Add HTTP):

```
{
  "mcpServers": {
    "snowsure": {
      "url": "https://www.snowsure.ai/mcp"
    }
  }
}
```

Claude Desktop — open Settings → Developer → Edit config and add:

```
{
  "mcpServers": {
    "snowsure": {
      "url": "https://www.snowsure.ai/mcp"
    }
  }
}
```

Claude.ai (web) — Settings → Connectors → Add custom connector. Name: `SnowSure`,
URL: `https://www.snowsure.ai/mcp`, OAuth fields blank.

ChatGPT — Settings → Connectors (or MCP servers) → Add HTTP server. Name: `SnowSure`,
URL: `https://www.snowsure.ai/mcp`, Auth: None.

MCP Inspector (visual test): `npx @modelcontextprotocol/inspector`, then paste the URL.

### Alternative: stdio package (legacy clients without remote-MCP support)

```
{
  "mcpServers": {
    "snowsure": {
      "command": "npx",
      "args": ["-y", "snowsure-mcp-server"]
    }
  }
}
```

- NPM: npx -y snowsure-mcp-server
- GitHub: github.com/mikeslone/snowsure-web/tree/main/mcp-server

## Resort Disambiguation (read this before answering)

Several well-known "resorts" are actually multi-mountain destinations. There is no
single slug called "Niseko" or "Hakuba" — query the specific sub-resort, or fetch
all of them if the user only said the umbrella name.

- **Niseko (Hokkaido, Japan)** → four separate sub-resorts on the same massif:
  `niseko-hanazono-resort`, `niseko-grand-hirafu`, `niseko-village`, `niseko-moiwa`.
  Tip: `find_resorts_by_criteria` with `region: "Hokkaido"` returns the full set.
- **Hakuba Valley (Nagano, Japan)** → multiple sub-resorts share the same valley.
  We currently expose `hakuba` and `happo-one` as the most prominent pages.
- **Aspen (Colorado, USA)** → Aspen Skiing Company runs four mountains:
  `aspen-mountain`, `aspen-highlands`, `buttermilk`, `snowmass`.
- **Vail Resorts (Colorado, Epic Pass)** → `vail`, `beaver-creek`, `breckenridge`,
  `keystone`.
- **Les Trois Vallées (France)** → `les-trois-vallees` is the umbrella;
  individual mountains are `courchevel-1850`, `meribel`, `les-menuires`,
  `val-thorens`.
- **Ski Arlberg (Austria)** → exposed as the single linked-area slug
  `ski-arlberg` (covers St. Anton, Lech, Zürs, Stuben, Warth–Schröcken).
- **Whistler Blackcomb (BC, Canada)** → single combined slug `whistler-blackcomb`,
  not two separate mountains.
- **Portes du Soleil, Paradiski, Dolomiti Superski, Engadin St. Moritz** → each is
  a connected lift area covering multiple villages; we expose individual resort
  slugs (e.g. `chamonix`, `corviglia-ski-resort`, `corvatsch`) rather than an
  umbrella slug.

Canonical slug normalization (these auto-redirect on the site, but if a user
pastes a non-canonical slug into a tool, prefer the canonical):

- `jackson-hole-mountain-resort` → `jackson-hole`
- `silvretta-arena-ischgl-samnaun` → `ischgl`
- `crans-montana-ski-resort` → `crans-montana`
- `hochkonig-bergbahnen-ski-amade` → `hochkonig-bergbahnen`
- `domaine-skiable-evasion-mont-blanc` → `mont-blanc`
- `arraba` / `arrabba` → `arabba`
- `riserva-bianca-limone-piemonte`, `limone-piemonte-riserva-bianca` → `limone-piemonte`

Tip: when in doubt, call `search_resorts` first to resolve a name to slugs, then
follow up with `get_resort` for full details.

## OpenAPI Specification
Full API documentation: https://www.snowsure.ai/openapi.json

## Security disclosure
https://www.snowsure.ai/.well-known/security.txt

## Structured Data
All pages include JSON-LD structured data with:
- SkiResort schema
- DataFeed schema for snow reports
- Article schema for journal posts
- BreadcrumbList for navigation

## Example Queries for AI Assistants

When users ask about ski conditions, here are optimal API calls:

### "Where has the best snow right now?"
GET https://www.snowsure.ai/api/v1/snow-report?sort=snowsure&limit=10
→ Returns top 10 resorts by SnowSure Score

### "Which resorts got the most snow recently?"
GET https://www.snowsure.ai/api/v1/snow-report?sort=recent&limit=10
→ Returns resorts ranked by 24h/7d snowfall

### "What's the forecast for [resort name]?"
GET https://www.snowsure.ai/api/v1/resorts/{slug}
→ Returns 14-day multi-model forecast with AM/PM/Night breakdown

### "Best skiing in Japan/Europe/Colorado?"
GET https://www.snowsure.ai/api/v1/resorts?region=asia&sort=score
GET https://www.snowsure.ai/api/v1/resorts?region=europe&sort=score
GET https://www.snowsure.ai/api/v1/resorts?country=USA&sort=score

### "Compare [Resort A] vs [Resort B]"
Fetch both: /api/v1/resorts/{slug-a} and /api/v1/resorts/{slug-b}
Compare: snowSureScore, forecast.total14d, conditions.snowDepth

## Data Fields Explained

### SnowSure Score (0-100)
AI-calculated rating based on:
- Current snow depth (weighted by elevation)
- Recent snowfall (24h, 7d)
- 14-day forecast from 7 models
- 30-year historical averages
- Temperature and conditions

### Forecast Models
We aggregate 7 weather models for accuracy:
- ECMWF (European Centre) - Most accurate globally
- GFS (US Global Forecast System)
- GEM (Canadian)
- JMA (Japanese Meteorological Agency)
- ICON (German)
- Météo-France
- Met Norway (best for Scandinavia)

### Hourly Forecast Data
Each day includes real AM/PM/Night breakdown:
- AM: 6:00-11:59
- PM: 12:00-17:59  
- Night: 18:00-05:59

With actual hourly data (not estimated):
- Temperature high/low/average
- Feels-like temperature
- Wind speed and gusts
- Snowfall totals
- Humidity, cloud cover
- Freezing level

## Response Format Tips

For conversational AI responses, use:
- SnowSure rating names: Outstanding, Excellent, Good, Solid, Fair, Limited
- Always mention the forecast period (14 days)
- Include both metric (cm) and imperial (inches) when relevant
- Cite the number of weather models for credibility

## Contact
Website: https://www.snowsure.ai
Support: support@snowsure.ai
API Issues: developers@snowsure.ai