Vinkius

NOAA Climate MCP. Analyze historical weather trends across decades.

NOAA Climate — Historical Weather Records provides access to the planet's largest archive of daily weather data, including temperature, precipitation, snow depth, and wind records for over 100,000 stations worldwide. You can retrieve detailed daily readings (GHCN-Daily), monthly averages (GSOM), or yearly summaries (GSOY) spanning decades. It also provides 30-year climate normals and station searches, making it the definitive source for historical climate science analysis.

NOAA Climate MCP is compatible with Claude Claude
NOAA Climate MCP is compatible with ChatGPT ChatGPT
NOAA Climate MCP is compatible with Cursor Cursor
NOAA Climate MCP is compatible with Gemini Gemini
NOAA Climate MCP is compatible with Windsurf Windsurf
NOAA Climate MCP is compatible with VS Code VS Code
NOAA Climate MCP is compatible with JetBrains JetBrains
NOAA Climate MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Fetch detailed daily weather readings

Retrieve specific measurements like maximum/minimum temperature and precipitation totals for any given date range and station.

Calculate monthly climate averages

Generate aggregate summaries that provide average temperatures, total rainfall, or heating degree days for an entire month.

Determine yearly climate trends

Get year-over-year data points, including annual temperature averages and extreme weather values.

Establish baseline 'normal' conditions

Access the statistical 30-year baseline (1991–2020) to compare current readings against historical norms for a location.

Locate weather stations globally

Search NOAA's network to find specific station IDs, names, and geographical coordinates needed for all other data calls.

Waiting for input…

AI Agent
NOAA Climate

What AI agents can do with NOAA Climate — Historical Weather Records (5 Tools)

These five tools allow your AI agent to interact with NOAA's full range of climate data, letting you analyze everything from daily temperature spikes to multi-decade averages.

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 NOAA Climate — Historical Weather Records MCP

Get Daily Data

Pulls daily temperature, precipitation, snow depth, and wind records for specific dates at a given station.

Get Monthly Summary

Generates monthly aggregates of average temperature, total rainfall, and heating...

Get Yearly Summary

Provides annual summaries detailing yearly averages and extreme values for long-term...

Get Climate Normals

Retrieves the standard 30-year statistical baseline (1991-2020) that defines...

Search Stations

Finds official NOAA station IDs and coordinates using a location name or bounding...

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.

NOAA Climate 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 NOAA Climate 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 NOAA Climate — Historical Weather Records, 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
NOAA Climate 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 NOAA. 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.

Climate data analysis used to involve massive spreadsheets and API juggling.

Before this MCP, analyzing climate trends meant downloading huge CSV files from NOAA's site. You'd spend hours cleaning the data—matching station IDs across different time periods, ensuring consistent date formats, and manually compiling summaries for comparison. It was a tedious cycle of copy-pasting, cross-referencing years, and arguing with spreadsheet formulas.

Now, you ask your agent to compare 1950 rainfall totals against today's readings. The MCP handles the data retrieval complexity: it uses `search_stations` to find the right ID, then calls `get_yearly_summary` for both dates. You don't see the API calls; you just get the clean comparison you need.

Get immediate climate baselines with NOAA Climate — Historical Weather Records MCP

The most time-consuming part was establishing a reliable 'normal.' You had to manually determine which 30-year window the data used. This process introduced human error and slowed down research considerably.

With this MCP, running `get_climate_normals` instantly gives you the standardized 1991–2020 baseline for any station. You get reliable scientific context in seconds, letting you focus on interpreting the results instead of cleaning the inputs.

What NOAA Climate MCP does for your AI

This MCP gives your agent direct access to NOAA's massive archive of global weather data. Forget sifting through dozens of academic databases or piecing together yearly reports. You can ask specific questions like, 'How did average rainfall change in Miami between 1980 and 2000?' The system pulls the raw historical records—daily temperature highs, precipitation totals, and snow accumulation—and formats them for immediate use.

Whether you need a full year's worth of data or just the baseline thirty-year normal, this MCP handles it. You can pinpoint exact stations anywhere in the world and run analyses across daily, monthly, or annual scales. By connecting to Vinkius, you get all these climate tools under one roof, letting your AI client treat NOAA as a single, unified source for everything from local microclimates to continental trends.

Built · Hosted · Managed by Vinkius NOAA Climate Records - Historical Weather Data MCP
Server ID 019d75de-768e-7362-83b4-57e2442dba59
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about NOAA Climate MCP

How do I find a specific NOAA weather station ID using NOAA Climate — Historical Weather Records MCP? +

You must start by calling search_stations. This tool accepts location names or bounding boxes and returns the exact, necessary station IDs for every other data retrieval tool.

What is the difference between using get_daily_data and get_monthly_summary with NOAA Climate — Historical Weather Records MCP? +

get_daily_data gives you granular records (max/min temp, precipitation) for every day. get_monthly_summary aggregates this data to give you averages and totals for the entire month, which is better for spotting general trends.

Can I use NOAA Climate — Historical Weather Records MCP to compare temperatures across different years? +

Yes. You can use get_yearly_summary repeatedly across different decades (e.g., 1950 vs. 2020) to track yearly averages and extreme values.

Does get_climate_normals cover all historical data? +

No, get_climate_normals provides the standardized statistical baseline (1991-2020). It is a reference point, not raw historical data.

What if I need precipitation records for many different stations? +

First, you run search_stations to get the list of all required IDs. Then, your agent can iterate through that list, calling get_daily_data or get_monthly_summary for each ID and date range.