# Smarterweather Weather MCP server

Source: https://glimind.com/server/mcp-registry%2Fio.github.smarterweather%2Fweather
Registry id: `mcp-registry/io.github.smarterweather/weather`
Status: live (checked 2026-10-27T02:43:03.491Z)

## Verdict

Smarterweather Weather MCP server answered 100% of Glimind's liveness checks over 30 days, better than 42% of MCP servers, with 665 ms median handshake and 1 outage in 90 days. Its agent-readiness grade is A (92/100) across 16 tools, costing an agent about 6,132 tokens to load. Checked every few minutes; no tool is ever called.

## Measurements (30 days)

| Metric | Value | Better than |
|---|---|---|
| Uptime, 30 days | 100% | 42% of MCP servers |
| Median handshake latency | 665 ms | 37% of MCP servers |
| p95 handshake latency | 3162 ms | — |
| Checks in 30 days | 5,038 | — |
| Outages, 90 days | 1 | — |
| Median recovery | 4 min | — |
| Agent-readiness score | 92/100 (A) | 73% of MCP servers |
| Tools | 16 | — |
| Tool-list size for an agent | ~6,132 tokens | 36% of MCP servers |
| Days observed | 29 | — |

## Install

```json
{
  "mcpServers": {
    "smarterweather-weather-mcp-server": {
      "type": "http",
      "url": "https://mcp.smarterweather.com"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http smarterweather-weather-mcp-server https://mcp.smarterweather.com
```

## Tools (16)

- `call_tool`: Runs a tool find_tools lists, by name: same price, limits and result as calling it directly. Tools already in your list are called directly, not through this. `
- `describe_dataset`: A dataset's variables (standard names, units, display units, categories, bands), horizon, step, cadence, freshness, cost class and an example_query for query_da
- `find_tools`: Lists the weather tools this connection does not show (best times, comparisons, forecast totals, air quality; station observations, soundings, hurricane recon; 
- `get_alerts`: NWS watches, warnings, advisories. Point (city/ZIP/lat+lon): containing polygons. BBox or US state/DC/CONUS (codes, full names, US/national): intersecting polyg
- `get_current_conditions`: Current weather right now at a location from two independent sources in one call: the RTMA gridded analysis (exact-point values, updated sub-hourly) and the nea
- `get_forecast`: Complete weather overview for a location: current conditions, daily forecast (SPC threats, severity; view "detailed" adds CAPE, UV, full day/night periods), act
- `get_forecast_distribution`: NBM probabilistic guidance for one weather aspect: percentiles (p10-p90), exceedance probabilities and ensemble spread. Use this for any question about odds, ra
- `get_hourly_forecast`: Blended hourly forecast: temperature, feels-like, humidity, wind, precipitation probability/amount, conditions, and icon per hour. hourly[0] is the current or n
- `get_observed_precipitation`: How much rain fell: observed precipitation totals at a location. Use for "did it rain", "how much rain fell", "rain in the last 24 hours / since yesterday". Sou
- `get_platform_status`: Current data-freshness status of the weather platform: overall state, per-source states (ok / degraded / outage / no_signal), open incidents with cause attribut
- `get_time_context`: Complete temporal context for a location: local time, timezone, 14-day calendar with day names and Today/Tomorrow offsets, sunrise/sunset/solar times (from the 
- `list_datasets`: Discover the gridded datasets (model grids, analyses) available at a location, or every public one when none is given, keyed by dataset_id. At a point: its doma
- `query_dataset`: Raw time series of one dataset's variables at a point, with unit labels: any gridded product (NBM, HRRR, RRFS, GFS, RTMA, MRMS, air quality, ...). Time modes: h
- `reverse_geocode`: Resolve coordinates to a human-readable place (city, state, county, timezone). Use when you have lat/lon but need a display name or the local timezone. Example:
- `search_catalog`: Find which dataset answers a weather question when no dedicated tool fits: ranks the data catalog (model grids, radar, satellite, outlooks, observations) by the
- `search_locations`: Resolve a place to ranked candidates with lat/lon: city ("Denver"), "city, ST", ZIP ("50219"), or partial input with fuzzy=true ("bost" -> Boston); venues and a

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.