Open-Meteo MCP Server

Give any LLM accurate weather data: forecasts, history back to 1940, air quality, marine conditions, floods and climate projections.

Features • Getting started • Tools • Remote deployment • Configuration • Development

A Model Context Protocol server for the free Open-Meteo APIs. Plug it into Claude Desktop, Claude Code or any MCP client, then ask in plain language:

What were the temperatures in London during January 2023?
Compare the ICON and GFS ensemble forecasts for Berlin over the next 5 days.
Give me the current European AQI, UV index and pollen levels in Paris.

No API key is needed: Open-Meteo is free for non-commercial use.

Features

• 17 tools covering forecasts, ERA5 history, air quality, marine, flood, seasonal, ensemble and CMIP6 climate data, plus geocoding and elevation
• Model-specific forecasts from DWD ICON, NOAA GFS, Météo-France, ECMWF, JMA, MET Norway and Environment Canada GEM
• Built for LLMs: strict input schemas, server instructions that tell the model which tool answers which question, compact JSON responses capped at 25,000 characters
• Two transports: stdio for local clients, stateless Streamable HTTP for remote deployments, with API key auth, rate limiting and origin checks
• In-memory response cache with per-endpoint TTLs, so repeated questions don't hit Open-Meteo again
• Self-hosting friendly: every Open-Meteo endpoint can point at your own instance

Getting started

You need Node.js 22 or later. Nothing to install beforehand: npx fetches the server on first run.

Claude Desktop

Add the server to your claude_desktop_config.json:

{
  "mcpServers": {
    "open-meteo": {
      "command": "npx",
      "args": ["-y", "-p", "open-meteo-mcp-server", "open-meteo-mcp-server"]
    }
  }
}

Claude Code

claude mcp add open-meteo -- npx -y -p open-meteo-mcp-server open-meteo-mcp-server

Other MCP clients

Any client that launches stdio servers works with the same command: npx -y -p open-meteo-mcp-server open-meteo-mcp-server. You can also install it globally with npm install -g open-meteo-mcp-server and run open-meteo-mcp-server.

Tip

Every data tool takes coordinates. Ask with a place name and the model will call geocoding first to resolve it.

Tools

Category	Tool	What it answers
Core	weather_forecast	Forecast up to 16 days, picking the best model for the location. Recent past via past_days (up to 92)
	weather_archive	Historical weather from 1940 to yesterday (ERA5 reanalysis)
	air_quality	PM2.5, PM10, ozone, NO₂, pollen, European and US AQI, UV index
	marine_weather	Wave height, period and direction, swell, sea surface temperature
	geocoding	Place name or postal code to coordinates
	elevation	Terrain height for coordinates
Models	dwd_icon_forecast	DWD ICON (Germany, high resolution over Europe)
	gfs_forecast	NOAA GFS (global, high resolution over North America)
	meteofrance_forecast	Météo-France AROME and ARPEGE
	ecmwf_forecast	ECMWF IFS and AIFS
	jma_forecast	Japan Meteorological Agency
	metno_forecast	MET Norway (Nordic countries)
	gem_forecast	Environment Canada GEM
Advanced	ensemble_forecast	Forecast uncertainty across ensemble members. models is required
	seasonal_forecast	Outlook from a few weeks to about 7 months ahead
	climate_projection	CMIP6 climate projections, 1950 to 2050
	flood_forecast	River discharge from GloFAS

weather_forecast is the default choice. The model-specific tools are for when a particular model is asked for, or to compare models with one call each.

Responses

• Times are GMT unless timezone is set. timezone: "auto" uses the location's local time.
• null in a series means the model has no value for that time, not zero.
• Responses over 25,000 characters have their hourly / daily / minutely_15 arrays shortened by the same ratio, keeping series aligned, and gain truncated: true with a truncation_message. Narrow the date range or the variables to get everything.

The full list of variables and parameters is in each tool's input schema and in the Open-Meteo documentation.

Remote deployment

Set TRANSPORT=http to serve MCP over Streamable HTTP at /mcp instead of stdio:

TRANSPORT=http HOST=0.0.0.0 PORT=3000 API_KEY=your-secret-key npx open-meteo-mcp-server

Clients then send the key with every request, as Authorization: Bearer <key> or X-API-Key: <key>. GET /health answers {"status":"ok"} without a key, for container probes.

The transport is stateless: each POST /mcp is handled on its own, no session ID is issued, and GET / DELETE /mcp answer 405. No tool keeps state between calls, so clients lose nothing.

Important

The server binds to 127.0.0.1 by default, so it is reachable only from the local machine. Set HOST=0.0.0.0 to accept remote connections, and set API_KEY whenever you do: without it, the server runs in open mode.

Docker

A prebuilt image is published to the GitHub Container Registry. It already binds to 0.0.0.0:

docker run -d --name open-meteo-mcp -p 3000:3000 \
  -e API_KEY=your-secret-key \
  ghcr.io/cmer81/open-meteo-mcp:latest

Tags follow the npm version without the v prefix: latest, 2.5.1, 2.5, 2.

The repository also has docker-compose.yml (prebuilt image) and docker-compose.dev.yml (builds from source). Copy .env.example to .env to configure them.

claude.ai traffic

Every claude.ai user reaches a remote server from Anthropic's outbound range 160.79.104.0/21. That range gets its own rate-limit pool (RATE_LIMIT_ANTHROPIC_RPM) so they don't all share one per-IP budget. Behind a reverse proxy, list the proxy in TRUSTED_PROXIES so the real client IP is seen.

Configuration

All variables are optional.

Server

Variable	Default	Description
TRANSPORT	stdio	http for Streamable HTTP
PORT	3000	HTTP port
HOST	127.0.0.1	Interface to bind. 0.0.0.0 accepts remote connections
OPEN_METEO_CACHE_MAX_BYTES	20000000	Response cache size, in bytes of serialized JSON. 0 disables it

The cache keeps forecasts and ensembles for 15 minutes, air quality and marine for 30 minutes, flood for 1 hour, seasonal for 6 hours, archive and climate for 24 hours, geocoding for 7 days and elevation for 30 days. Archive ranges ending within the last 5 days are kept for 1 hour only, since Open-Meteo is still backfilling them. Failed requests are never cached.

Note

The cache counts serialized JSON, but the parsed objects in memory take about 1.2 to 2.6 times as much. A full cache at the default size costs about 50 MB of heap.

HTTP security

Variable	Default	Description
API_KEY	unset (open)	Key required on every /mcp request
RATE_LIMIT_RPM	60	Requests per minute per client IP. IPv6 clients are grouped by /56
RATE_LIMIT_ANTHROPIC_RPM	600	Requests per minute shared by all claude.ai traffic
TRUSTED_PROXIES	unset	Comma-separated IPs or CIDRs whose X-Forwarded-For is trusted
ALLOWED_ORIGINS	empty	Comma-separated browser origins allowed. Any request with an unlisted Origin header gets 403 (DNS rebinding protection). Requests without one are unaffected

Custom Open-Meteo instance

Each endpoint can be redirected, for example to a self-hosted Open-Meteo:

Variable	Default
OPEN_METEO_API_URL	https://api.open-meteo.com
OPEN_METEO_ARCHIVE_API_URL	https://archive-api.open-meteo.com
OPEN_METEO_AIR_QUALITY_API_URL	https://air-quality-api.open-meteo.com
OPEN_METEO_MARINE_API_URL	https://marine-api.open-meteo.com
OPEN_METEO_SEASONAL_API_URL	https://seasonal-api.open-meteo.com
OPEN_METEO_ENSEMBLE_API_URL	https://ensemble-api.open-meteo.com
OPEN_METEO_GEOCODING_API_URL	https://geocoding-api.open-meteo.com
OPEN_METEO_FLOOD_API_URL	https://flood-api.open-meteo.com
OPEN_METEO_CLIMATE_API_URL	https://climate-api.open-meteo.com

In Claude Desktop, pass them through the env key of the server entry.

Skills

The skills/ directory holds two SKILL.md guides that help an assistant pick the right tool and parameters:

Skill	Best for
open-meteo	Everyday weather: forecasts, history, air quality, marine, elevation
open-meteo-advanced	Specific models, ensemble uncertainty, seasonal outlooks, climate projections

For Claude Code, copy them to ~/.claude/skills/:

cp -r skills/open-meteo skills/open-meteo-advanced ~/.claude/skills/

For Claude Desktop, upload the relevant SKILL.md into the conversation.

Development

git clone https://github.com/cmer81/open-meteo-mcp.git
cd open-meteo-mcp
npm install
npm run build

Command	Description
npm run dev / npm run dev:http	Run from source with auto-reload (stdio / HTTP)
npm test	Unit tests (network mocked)
npm run typecheck / npm run lint	Type checking and Biome linting
npm run smoke	Calls all 17 tools against the live API through a real MCP client. Needs a prior build
npm run eval	LLM-usability benchmark, see below

To point Claude Desktop at your local build, use "command": "node" with "args": ["/path/to/open-meteo-mcp/dist/index.js"].

Evaluations

evals/evaluation.xml checks whether an LLM given only this server's tools can answer realistic questions. Its 14 questions rely on stable data (ERA5 archive, CMIP6 projections, geocoding, elevation), so the expected answers don't drift.

pip install -r evals/scripts/requirements.txt
export ANTHROPIC_API_KEY=...        # or put it in .env

npm run build && npm run eval
npm run eval -- --no-server-instructions   # baseline without the server instructions

Warning

The evaluation calls the real Anthropic API for every question and consumes credits. It is a manual check, not part of CI.

Contributions are welcome: see CONTRIBUTING.md.