# meteoswiss-llm-tools

> meteoswiss-llm-tools — eins78-meteoswiss-llm-tools. Use this tool when you need to leverage Meteoswiss open data for large language models (LLMs) to access weather-related information and solve problems related to climate and meteorology. It provides an interface to the MCP server, allowing for seamless integration of weather data into LLM applications. Ideal for use cases requiring accurate and reliable weather forecasts, climate analysis, or meteorological data processing.

Canonical page: https://skillsregistry.net/skills/eins78-meteoswiss-llm-tools  
JSON: https://api.skillsregistry.net/v1/skills/eins78-meteoswiss-llm-tools

## Description

Meteoswiss Open Data Tools for LLMs - MCP server and Agent Skill

## Trust

- **Trust score (0–1):** 0.95
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-26

## Source

- **Source listing:** [GitHub](https://github.com/eins78/meteoswiss-llm-tools)

## 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": "eins78-meteoswiss-llm-tools"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/eins78-meteoswiss-llm-tools` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/eins78-meteoswiss-llm-tools/pull`

---
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