Vinkius

Open-Meteo Historical Weather MCP. Analyze 84 Years of Global Climate Data

Open-Meteo Historical Weather gives you access to 84 years of global climate data, covering everything from temperature and humidity to wind patterns and rainfall. You can pull detailed hourly records or broad daily averages for any location on Earth, making it the ultimate resource for long-term climate research and risk modeling.

Open-Meteo Historical Weather MCP is compatible with Claude Claude
Open-Meteo Historical Weather MCP is compatible with ChatGPT ChatGPT
Open-Meteo Historical Weather MCP is compatible with Cursor Cursor
Open-Meteo Historical Weather MCP is compatible with Gemini Gemini
Open-Meteo Historical Weather MCP is compatible with Windsurf Windsurf
Open-Meteo Historical Weather MCP is compatible with VS Code VS Code
Open-Meteo Historical Weather MCP is compatible with JetBrains JetBrains
Open-Meteo Historical Weather MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Calculate historical weather metrics

Retrieve comprehensive hourly and daily climate records (temperature, wind speed, precipitation) for any specified location and date range.

Analyze long-term temperature trends

Focus on apparent temperature data to model how average temperatures have shifted over decades or centuries at a specific site.

Generate daily weather summaries

Get aggregated historical records, including maximum and minimum temperatures, total precipitation, and sunshine duration for any given day.

Waiting for input…

AI Agent
Open-Meteo Historical Weather

What AI agents can do with Open-Meteo Historical Weather: 3 Tools

Use these three specialized tools to retrieve comprehensive historical weather metrics, from general records to dedicated temperature trend analysis.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Open-Meteo Historical Weather MCP

Get Historical Weather

Gets comprehensive weather data—including temperature, humidity, wind, and rain—for any date range over 84 years of global records.

Get Historical Daily

Retrieves summarized daily weather reports, providing max/min temperatures, total...

Get Historical Temperature

Focuses on climate trend analysis by retrieving detailed historical data on...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Open-Meteo Historical Weather MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Open-Meteo Historical Weather integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Open-Meteo Historical Weather, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Open-Meteo Historical Weather MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Open-Meteo. 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.

VINKIUS CLOUD

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Manually tracking historical climate data is a nightmare of clicks.

Today, analyzing long-term weather shifts means opening multiple academic databases. You're clicking through reports for rainfall totals on one tab, max temperatures on another, and then cross-referencing wind speed from a third source—all while copy-pasting dates and coordinates into a spreadsheet.

With this MCP, the process is simple: you ask your agent for the data range and type of metric. It pulls everything together automatically. You get clean, structured climate records ready for modeling in minutes.

Open-Meteo Historical Weather gives you the full picture.

You no longer have to worry about whether a single source provides hourly data or only daily aggregates. The MCP handles general records with `get_historical_weather`, dedicated summaries via `get_historical_daily`, and specialized trend metrics using `get_historical_temperature`.

Your workflow shifts from spending hours gathering fragmented data points to actually analyzing the patterns that matter.

What Open-Meteo Historical Weather MCP does for your AI

This MCP lets your agent access decades of continuous weather history for any place you name. Forget looking up data across multiple physical archives; here you get a single stream of reliable global records dating back to 1940. You can run complex analyses, comparing how rainfall changed between two different decades in the same city or calculating average temperature shifts over fifty years.

Whether you're modeling risk for insurance policies, tracking agricultural yield changes, or just curious about historical climate patterns, this MCP handles the heavy lifting. It provides dedicated tools to retrieve general weather metrics across a date range, pull specific daily aggregates like max/min temperatures, and focus purely on long-term temperature trends.

Connecting Open-Meteo Historical Weather through Vinkius means your agent has access to one of the largest catalogs of specialized data sources available.

Built · Hosted · Managed by Vinkius Open-Meteo Historical Weather - 84 Years of Climate Data
Server ID 019d75e8-2ba7-71ca-b449-3d5ba7ffe462
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Open-Meteo Historical Weather MCP

How far back can I go with Open-Meteo Historical Weather? +

The MCP covers 84 years of continuous records, going back to 1940. This range is suitable for nearly any long-term climate study.

Do I need coordinates or just city names for get_historical_weather? +

You must provide the exact latitude and longitude coordinates for all historical queries to ensure accurate data retrieval. City names aren't specific enough.

What difference is there between get_historical_daily and get_historical_temperature? +

Daily retrieves general aggregates like total precipitation and max/min temps for a day. Temperature focuses specifically on apparent temperature data, which is better for long-term climate trend analysis.

Can I compare two different cities using Open-Meteo Historical Weather? +

Yes. You simply run separate queries for the coordinates of each city and then use your agent to synthesize the resulting time series data into a single comparison report.

Is the weather data in get_historical_weather hourly or daily? +

Depending on the parameters you provide, get_historical_weather can deliver both comprehensive hourly records and broader daily summaries.