# Meteomatics

> Use this tool when you need to access accurate and secure weather data for informed decision-making. The Meteomatics MCP server solves problems related to weather data integration, providing AI agents with a secure interface to request weather data through a standardized protocol. It accepts authentication inputs via OAuth and outputs relevant weather data, models, and parameters, making it ideal for use cases requiring reliable weather information.

Canonical page: https://skillsregistry.net/skills/meteomatics-meteomatics  
JSON: https://api.skillsregistry.net/v1/skills/meteomatics-meteomatics

## Description

The Meteomatics MCP (Model Context Protocol) server allows AI agents to securely access Meteomatics weather data tools. MCP is an open standard that lets AI applications connect to external tools and data sources. With the Meteomatics MCP, agents can request weather data directly from the Meteomatics API through a secure /mcp endpoint.

The MCP server manages authentication using OAuth (client registration, authorization code + PKCE, and refresh tokens). Once connected, the AI agent can access data, models, parameters, time ranges that are available to your Meteomatics API account.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/meteomatics/meteomatics)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "meteomatics-meteomatics"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/meteomatics-meteomatics` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/meteomatics-meteomatics/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt