# NOAA Forecast MCP

> The NOAA Forecast MCP provides access to official National Weather Service data covering all US locations. You can pull 7-day daily forecasts, detailed 156-hour hourly conditions, raw quantitative grid arrays (for temperature, wind, precipitation), and technical Area Forecast Discussions from over a dozen offices. It gives your agent comprehensive weather context for any task.

## Overview
- **Category:** the-unthinkable
- **Price:** Free
- **Tags:** weather-forecasting, meteorology, nws-forecast, grid-data, hourly-weather, climate-modeling

## Description

This MCP connects your AI client directly to the official National Weather Service forecast engine. Instead of relying on general search results or limited third-party APIs, you get raw, authoritative data sourced from NWS meteorologists and technical grids.

When running an agent through Vinkius, it can interpret complex requests—like comparing 7-day averages with hourly probability changes across a specific region. You're not just fetching a single number; you're pulling structured arrays of temperature, wind speed, precipitation chance, and detailed narrative reports from the official offices.

Your agent uses this MCP to gather everything needed, whether it’s running a programmatic analysis on raw grid data or summarizing complex discussion notes. It means your AI client can handle multi-layered weather reporting for any US location without needing an API key or manual setup.

## Tools

### get_forecast
Generates a standard 7-day weather summary for any U.S. location using latitude and longitude, including highs/lows and wind direction.

### get_hourly_forecast
Retrieves detailed hour-by-hour conditions covering five days, listing temperature, humidity, and precipitation chance for a U.S. location.

### get_forecast_discussion
Fetches the technical Area Forecast Discussion (AFD) from specific NWS offices using their 3-letter code.

### get_grid_data
Provides raw quantitative weather data arrays, allowing for deep programmatic analysis of temperature, wind, and humidity across the U.S.

### get_point_metadata
Retrieves specific NWS metadata about a US location, identifying its responsible Weather Forecast Office (WFO) and grid coordinates.

## Prompt Examples

**Prompt:** 
```
What's the weather forecast for New York City this week?
```

**Response:** 
```
🌤️ **NYC 7-Day Forecast**

Today: Partly cloudy, High 72°F, Wind SW 10 mph
Tonight: Clear, Low 58°F
Wednesday: Sunny, High 78°F
Thursday: Thunderstorms, High 74°F, 60% chance rain
Friday: Clearing, High 68°F
Weekend: Sunny, Highs 72-75°F

Source: NWS Office OKX (Upton, NY)
```

**Prompt:** 
```
Get hourly forecast for Miami Beach
```

**Response:** 
```
⏰ **Miami Beach — Hourly Forecast**

| Hour | Temp | Wind | Rain |
|------|------|------|------|
| 2pm | 88°F | SE 12 | 10% |
| 3pm | 89°F | SE 14 | 20% |
| 4pm | 87°F | SE 15 | 40% |
| 5pm | 84°F | S 18 | 60% |
| 6pm | 82°F | S 12 | 30% |

Afternoon sea-breeze thunderstorms likely.
```

## Capabilities

### Retrieve 7-Day Forecast Details
Gets a daily summary including high/low temperatures, precipitation probability, and narrative descriptions for a specified US latitude and longitude.

### Get Hourly Weather Conditions
Pulls hour-by-hour data across 5 days, detailing temperature, wind direction, humidity levels, and sky conditions.

### Fetch Official Discussion Notes
Retrieves technical Area Forecast Discussions (AFD) from specific NWS Weather Forecast Offices using their three-letter code.

### Download Raw Grid Data Arrays
Grabs quantitative weather data arrays, useful for deep programmatic analysis of temperature, wind, and precipitation.

### Identify Location Metadata
Provides NWS metadata about a US location, including which Weather Forecast Office is responsible and the specific grid coordinates.

## Use Cases

### Planning a cross-state logistics route
A freight company needs to know if an interstate run through the Midwest will be impacted by severe weather. The agent calls get_hourly_forecast for all necessary waypoints, allowing the planner to adjust schedules and avoid predicted thunderstorm paths.

### Developing a climate model comparison
A university researcher needs to compare current atmospheric conditions against historical averages. They use get_grid_data to pull raw temperature and precipitation arrays for a specific grid area, enabling complex statistical modeling.

### Handling an emergency response deployment
Local government staff need immediate confirmation of the governing authority during a storm. The agent uses get_point_metadata first to identify the correct WFO, then runs get_forecast_discussion for actionable expert commentary.

### Building an automated weather report card
A media outlet needs a detailed daily digest. They use get_forecast and get_hourly_forecast in sequence to build a comprehensive narrative, starting with the general 7-day outlook and drilling down into hourly changes.

## Benefits

- Get the full picture with get_hourly_forecast, which provides a detailed timeline of conditions over five days, going far beyond simple daily high/low numbers.
- For deep analysis, use get_grid_data to pull raw arrays for temperature and wind. This lets your agent run complex calculations that standard weather summaries can't support.
- Understand the 'why' behind a forecast by running get_forecast_discussion. This tool gives access to technical text reports written by NWS meteorologists themselves.
- Never guess where a location falls in the system; use get_point_metadata to instantly confirm the responsible WFO and precise grid zone for any point in the U.S.
- The combination of getting 7-day weather forecast data with get_hourly_forecast means your agent can build complete, multi-scale operational reports from one source.

## How It Works

The bottom line is you get direct, standardized access to official NWS weather reporting for US locations, without needing keys or manual setup.

1. First, specify the required weather data type and provide the target US latitude and longitude. For example, you might ask for a 7-day forecast.
2. Next, your AI client executes the appropriate tool call against the NOAA engine; it handles the specific formatting required for raw grid arrays or office codes.
3. Finally, the MCP returns structured data—whether that's a table of hourly conditions or a technical text summary—which your agent can then interpret and use in its final output.

## Frequently Asked Questions

**What locations does NOAA Forecast — US Weather Predictions MCP cover?**
This MCP covers all United States locations, including Puerto Rico and other U.S. territories. It is restricted to NWS coverage areas.

**Do I need an API key for get_hourly_forecast using NOAA Forecast — US Weather Predictions MCP?**
No, the connection is completely open, meaning you don't need any registration or special keys to use the weather data tools.

**How do I check historical weather patterns with NOAA Forecast — US Weather Predictions MCP?**
This MCP provides current and forecast data. For accessing indexed historical records, you would need a different tool set designed for archival retrieval.

**Can get_point_metadata help me confirm the responsible NWS office code?**
Yes, this tool gives you critical metadata about any US location, including which Weather Forecast Office (WFO) is assigned to that grid coordinate.

**Is the data from get_forecast_discussion reliable for expert analysis?**
The discussion notes are technical Area Forecast Discussions (AFD) written by NWS meteorologists, providing highly authoritative context and explanation for current weather patterns.