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OpenWeather MCP. Access Global Weather Data via Your AI Agent.

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OpenWeather MCP on Cursor AI Code Editor MCP Client OpenWeather MCP on Claude Desktop App MCP Integration OpenWeather MCP on OpenAI Agents SDK MCP Compatible OpenWeather MCP on Visual Studio Code MCP Extension Client OpenWeather MCP on GitHub Copilot AI Agent MCP Integration OpenWeather MCP on Google Gemini AI MCP Integration OpenWeather MCP on Lovable AI Development MCP Client OpenWeather MCP on Mistral AI Agents MCP Compatible OpenWeather MCP on Amazon AWS Bedrock MCP Support

Just plug in your AI agents and start using Vinkius.

OpenWeather gives your AI agent global weather data. You get current conditions, 48-hour forecasts, air quality reports, and historical records for any location worldwide.

Use the `geocode` tool first to map city names to coordinates, then access everything else from a single chat prompt.

What your AI agents can do

Geocode

Converts a city name into the top 5 matching locations, providing coordinates, country codes, and state names.

Get air quality

Returns the current Air Quality Index (AQI) and pollutant concentrations for specified coordinates.

Get air quality forecast

Provides a 4-day air quality forecast, including AQI levels and pollutant concentration predictions.

+ 8 more capabilities included
Get Coordinates by City Name

The agent converts a user-provided city name (like 'Denver') into precise latitude/longitude coordinates required for subsequent lookups.

Check Current Environmental Conditions

You pull real-time data including temperature, wind speed, and atmospheric pressure for any given location or coordinate set.

Predict Air Quality Trends

The server returns the current AQI level and a four-day forecast detailing pollutant levels like PM2.5 and Ozone concentrations.

Retrieve Long-Term Weather Patterns

You can fetch up to 16 daily weather summaries, showing minimum/maximum temperatures and precipitation chances for planning.

Access Specific Historical Metrics

The agent fetches a full report (temp, humidity, wind) for an exact date in the past, using coordinates and a YYYY-MM-DD input.

Supported MCP Clients

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients
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AI Agent

OpenWeather MCP Server: 11 Tools for Global Weather Access

These tools let you access every metric needed—from current conditions to 16-day forecasts and pollutant levels—all managed by your AI client.

action019d8468

geocode

Converts a city name into the top 5 matching locations, providing coordinates, country codes, and state names.

get019d8468

get air quality

Returns the current Air Quality Index (AQI) and pollutant concentrations for specified coordinates.

get019d8468

get air quality forecast

Provides a 4-day air quality forecast, including AQI levels and pollutant concentration predictions.

get019d8468

get current weather

Retrieves real-time weather conditions (temperature, wind, pressure) for either a city name or coordinates.

get019d8468

get daily forecast

Gets a daily forecast spanning up to 16 days, reporting min/max temperatures and precipitation chance.

get019d8468

get forecast

Pulls a shorter-term weather prediction (up to 5 days / 3 hours) using either coordinates or city name.

get019d8468

get historical weather

Fetches specific weather metrics for an exact date in the past, requiring latitude/longitude and a YYYY-MM-DD format.

get019d8468

get hourly forecast

Generates a detailed hourly forecast using coordinates, including wind speed and UV index data.

get019d8468

get sun times

Calculates the exact times for sunrise and sunset, along with the sun's elevation angle, for given coordinates.

get019d8468

get weather alerts

Checks for active severe weather warnings, returning alert type, severity, and time windows based on coordinates.

reverse019d8468

reverse geocode

Converts a set of coordinates back into readable location details like city, state, country, and postal code.

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What you can do with this MCP connector

OpenWeather gives your agent global weather data. You pull real-time climate metrics and historical records for any location worldwide using this server.

First, you gotta map out where you are. If a user just throws a city name at ya—say, 'Miami' or 'Boston'—you run the geocode tool. It doesn't give you one answer; it spits back up to five matching locations, giving you precise coordinates, country codes, and state names for each match.

When you have those coordinates, you can start pulling data. You use reverse_geocode if you get coordinates but need the readable address—it converts lat/lon into city name, state, country, and postal code details.

Getting Current Conditions:
To check what's happening right now, you run get_current_weather. This pulls real-time data: temperature, wind speed, and atmospheric pressure. You can also use this tool with a simple city name if coordinates are unavailable.
For air quality right at this minute, you hit up the get_air_quality tool; it returns the current Air Quality Index (AQI) alongside pollutant concentrations like PM2.5 and Ozone levels.

Forecasting for Tomorrow:
If you need to look ahead, you've got options. For a quick glance at what's coming up, use get_forecast, which gives a short-term prediction covering up to five days in three-hour increments. You can also run the get_hourly_forecast tool for granular detail using coordinates; this spits out wind speed and UV index data hour by hour.
For planning further out, you've got get_daily_forecast, which gives a summary up to 16 days out, reporting minimum/maximum temperatures and the chance of precipitation.

If you just want a general forecast for a specific day without the hourly breakdown, run get_daily_forecast.

Air Quality Trends:
You don't just check today's air; you can predict it. The get_air_quality_forecast tool gives you a four-day look at air quality trends, predicting AQI levels and pollutant concentrations like PM2.5 over the next few days.

Historical Deep Dives & Safety:
For research or records, you use get_historical_weather. You gotta give it precise coordinates and an exact date in YYYY-MM-DD format; it then fetches specific metrics—temperature, humidity, wind speed—for that past day. If you need to know when the sun pops up or dips down, get_sun_times calculates those times, along with the sun's elevation angle, using coordinates.
If there's any heavy weather brewing, get_weather_alerts checks for active severe warnings and reports the alert type, severity level, and time window based on your provided location.

You can pull this whole package of data—current conditions, forecasts, air quality, and alerts—all from a single chat prompt after you get those coordinates.

How OpenWeather MCP Works

  1. 1 First, use geocode to turn a city name into required latitude/longitude pairs. You can't run any other tool without these coordinates.
  2. 2 Next, send your complex query (e.g., 'What was the air quality on May 1st?') and let your AI client select the right tool (get_air_quality, get_historical_weather) using those coordinates.
  3. 3 Finally, you get a synthesized report back—a single, complete answer that pulls data from multiple specialized tools.

The bottom line is: You tell your agent what you need; the server figures out which 1-2 specific tools to run and combines the results for you.

Who Is OpenWeather MCP For?

Anyone who relies on location data or planning—from travel logistics managers predicting transit conditions, to environmental researchers tracking pollution trends. It’s for the developer tired of stitching together 10 different API calls just to check a simple forecast.

Logistics Planner

Checks daily forecasts and weather alerts for cross-country shipping routes before committing resources.

Event Coordinator

Monitors UV index, hourly forecasts, and severe weather warnings to plan outdoor event safety protocols.

Environmental Data Scientist

Accesses historical weather data and 4-day air quality forecasts to run climate trend analyses.

What Changes When You Connect

  • Stop context switching. You get current conditions, daily forecasts, and alerts—all in one conversation flow using get_current_weather and get_daily_forecast. No manual API stitching required.
  • Handle complex queries like 'What was the pollution level last Tuesday?' The server supports this via get_historical_weather and get_air_quality, making deep research simple.
  • Build location-aware logic. If your user only gives a city name, let your agent run geocode first. This ensures all subsequent calls (like get_hourly_forecast) use the required coordinates.
  • Plan for safety and operations. Quickly check both active warnings (get_weather_alerts) and sun times (get_sun_times) to build robust operational checklists for outdoor work.
  • Analyze air quality trends efficiently. You can get a 4-day outlook using get_air_quality_forecast, which gives specific pollutant readings (PM2.5, Ozone) beyond just the general AQI number.

Real-World Use Cases

01

Checking travel safety across multiple metrics

A traveler asks: 'What's going to happen in Miami next week?' Your agent runs geocode first. Then, it calls get_daily_forecast for the 16-day outlook and supplements this by calling get_weather_alerts, giving a single safety summary.

02

Auditing historical environmental compliance

A researcher needs to know pollution levels during an industrial accident. They ask: 'What was the AQI in Phoenix on 2023-10-15?' The agent uses geocode and then calls get_historical_weather and get_air_quality together for a complete report.

03

Planning an outdoor festival layout

An event planner asks: 'What time should we start the main stage setup?' The agent uses geocode to nail down coordinates, then calls get_sun_times to get sunrise/sunset times and get_hourly_forecast for optimal lighting conditions.

04

Debugging location ambiguity

A user types 'Near the river.' The agent first runs reverse_geocode on a known coordinate set, identifying the city. It then uses that confirmed city name to get the current weather via get_current_weather, avoiding guesswork.

The Tradeoffs

Calling tools sequentially without routing

Trying to run get_daily_forecast and then passing a city name directly to get_air_quality. The latter tool needs coordinates, but you only gave it the forecast data.

Always check your inputs. If you start with a city name, use geocode first. Use the resulting latitude/longitude pair for all subsequent calls, like running both get_daily_forecast and get_air_quality.

Mixing forecast types

Asking for 'the 16-day forecast' and then expecting hourly data. The tools are specialized; the daily tool gives min/max, the hourly tool gives minute-by-minute readings.

Be specific about time granularity. If you need broad planning, use get_daily_forecast. If you need detailed movement prediction, run get_hourly_forecast.

Ignoring location ambiguity

Asking 'What's the weather in Los Angeles?' when your system could be talking about a different LA. The agent might fail or give vague results.

If possible, constrain the search with a state or country name. If not, let the agent run geocode first to confirm which specific location you mean.

When It Fits, When It Doesn't

Use this server if your workflow requires precise, multi-metric climate data and time-based lookups (e.g., 'What was the temp on X date?' or 'What's the AQI for the next 4 days?'). It’s built to handle complex dependencies: you must get coordinates first via geocode if your input is a city name, then decide which specific tool—forecast, air quality, historical—to run.

Don't use this if all you need is a general sentiment ('Is it going to be nice?') or simple unit conversions. For basic data retrieval without needing specialized forecasts (like just knowing the current temperature), standard weather apps are fine. If your task requires combining location lookup, time series data, and pollutant analysis, this server is what you need.

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by OpenWeather. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This server provides 11 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.

Available Capabilities

geocode get_air_quality get_air_quality_forecast get_current_weather get_daily_forecast get_forecast get_historical_weather get_hourly_forecast get_sun_times get_weather_alerts reverse_geocode

Checking global weather used to mean opening five different tabs.

Today, checking a simple forecast often means visiting the local news site for general conditions, then going to a separate air quality website for AQI, and maybe clicking another link just to find out if the sun rises early enough. It's fragmentation—you copy-paste coordinates or city names between services constantly.

With OpenWeather MCP, your agent handles that mess. You ask one question: 'What are the weather conditions in Seattle next week?' The system runs `geocode` internally, then pulls data from `get_daily_forecast`, combines it with a check of `get_weather_alerts`, and gives you one clean answer.

OpenWeather MCP Server: Accessing full climate data.

Before this, if you needed to run an analysis—say, comparing last year's pollution levels to today’s forecast—you had to manually find and input two distinct sets of coordinates, then make two separate API calls to different endpoints. It was a multi-step scripting chore.

Now, the agent handles that orchestration. You ask it for historical data (`get_historical_weather`) alongside current air quality (`get_air_quality`). The system manages the input parameters and stitches together a single, cohesive report.

Common Questions About OpenWeather MCP

How do I get an OpenWeather API key? +

Visit openweathermap.org/api, click Sign Up for a free account, go to API Keys in your account settings, and create a new key. Copy it — it's a 32-character hex string. Free tier includes 60 calls/minute.

Can I get weather alerts for my location? +

Yes! Use get_weather_alerts with lat/lon coordinates. Returns active alerts with sender name, event type, severity, description and start/end times. Useful for monitoring severe weather, floods, heat waves and other dangerous conditions.

Can I get historical weather data? +

Yes! Use get_historical_weather with lat/lon and a date in YYYY-MM-DD format. Returns the weather conditions for that specific day including temperature, humidity, wind and pressure.

How do I find coordinates for a city? +

Use geocode with the city name (e.g. 'London', 'São Paulo', 'Tokyo'). Returns the top 5 matching locations with their latitude, longitude, country code and state. Use these coordinates with other weather tools.

How does `get_air_quality_forecast` work to track pollution levels? +

The tool returns a four-day forecast detailing the AQI and key pollutants. You get concentrations for PM2.5, PM10, O3, NO2, SO2, CO, and NH3 across four consecutive days.

What inputs does `get_sun_times` require to calculate sunrise/sunset? +

You must provide latitude and longitude coordinates. The tool returns the exact times for both sunrise and sunset, along with the sun's elevation angle at those moments.

How can I use `reverse_geocode` if I only have coordinates? +

Just give the tool any set of lat/lon coordinates. It maps them back, returning the specific city name, state, country, and postal code for that precise location.

What information does `get_hourly_forecast` provide? +

This tool gives detailed data points every three hours over 48 hours. It includes temperature, humidity, wind speed, UV index, precipitation probability, and a condition description for each interval.

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