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Connect Meteostat to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Pull decades of climate records directly into your AI agent.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 10 capabilities

We ship only the actions that matter.

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 10 available through Meteostat.

  1. 01

    Stations nearby

    Find weather stations within a specific radius of your GPS coordinates.

  2. 02

    Point daily

    Get historical daily weather data for any specific geographic point.

  3. 03

    Point hourly

    Retrieve hourly weather observations for a specific coordinate.

  4. 04

    Point monthly

    Access monthly weather statistics for a specific location on Earth.

Capability set02 / 03

05-07

3 capabilities in this set.

Part of 10 available through Meteostat.

  1. 05

    Point normals

    Pull long-term climate normals for a specific point location.

  2. 06

    Stations daily

    Fetch up to 10 years of daily weather statistics for a specific station.

  3. 07

    Stations hourly

    Get up to 30 days of hourly weather observations from a station.

Capability set03 / 03

08-10

3 capabilities in this set.

Part of 10 available through Meteostat.

  1. 08

    Stations meta

    Retrieve metadata for a station using its ID, WMO, or ICAO identifier.

  2. 09

    Stations monthly

    Get monthly weather statistics for a specific station.

  3. 10

    Stations normals

    Access 30-year climate normals for a specific weather station.

Real work

What teams actually run

01

Environmental Research

Pull historical datasets to analyze how local weather has changed over time.

02

Logistics Optimization

Check past weather conditions for specific dates to plan more reliable routes.

03

App Development

Feed real-time or historical weather context into an agent-driven application.

04

Climate Baseline Studies

Use 30-year normals to compare current weather against historical averages.

Automate a task

Put Meteostat to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Meteostat works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Meteostat to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

1083ms average. Fast in production.

Meteostat is checked daily against the live service.

Daily averagePeak 1304ms
Oct 3Today
Fastest day
822ms
Slowest day
1304ms
14-day trend
Improving-9%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 10 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Meteostat, so you can see the experience inside your AI.

It does not authenticate your account with Meteostat. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Meteostat Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_JKO90Yyhey42dI7p2Gfm0lxPKzXASmcXKPATx7N7/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Meteostat capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "meteostat-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_JKO90Yyhey42dI7p2Gfm0lxPKzXASmcXKPATx7N7/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Meteostat in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Meteostat owners hand off.

This MCP is built for professionals who need to feed historical weather context into their analytical workflows.

  • 01

    Data Scientists

    They use the agent to pull large weather datasets for training machine learning models.

  • 02

    Logistics Planners

    They ask the agent to check historical weather patterns to optimize future routing.

  • 03

    Developers

    They use the agent to fetch weather context for apps without writing custom scrapers.

FAQ

Questions Meteostat owners ask.

  • 01

    How do I get weather data for a location without a station?

    You can use the point_hourly, point_daily, or point_monthly capabilities. These use interpolation to provide data for any specific coordinate on Earth.

  • 02

    What is the limit for daily station data requests?

    The stations_daily capability allows you to fetch up to 10 years of historical data per request.

  • 03

    Can I find stations near a specific GPS coordinate?

    Yes, the stations_nearby capability finds weather stations based on your provided GPS coordinates and a specified radius.

  • 04

    What kind of climate information is available?

    You can access 30-year climate normals for both specific stations and specific points via the stations_normals and point_normals capabilities.

  • 05

    Which AI clients can use this MCP?

    This MCP works with any compatible client, including Claude, Cursor, and Windsurf.

  • 06

    How can I find weather data for a location that doesn't have a specific weather station?

    You can use the point_hourly or point_daily capabilities. These capabilities use interpolation to calculate weather data for any geographic coordinate (latitude/longitude) by combining data from surrounding stations.

  • 07

    What is the difference between historical data and climate normals?

    Historical capabilities like stations_daily provide actual observations for specific dates. The stations_normals capability provides long-term statistical averages (usually over 30 years), which represent the 'typical' weather for a location.

  • 08

    Can I get weather data in Fahrenheit instead of Celsius?

    Yes. Most capabilities, such as stations_hourly and point_daily, include an optional units parameter. You can set this to 'imperial' to receive data in Fahrenheit and other non-metric units.

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