# MCPWeather

> Use this tool when you need to process and handle weather-related data requests, providing meteorological information through a configured MCP server. It solves problems related to accessing and retrieving weather data, enabling applications to receive timely and accurate meteorological updates. The MCPWeather tool accepts data requests as input and outputs relevant weather information via the Model Context Protocol interface.

Canonical page: https://skillsregistry.net/skills/adry22-mcpweather  
JSON: https://api.skillsregistry.net/v1/skills/adry22-mcpweather

## Description

Enables processing and handling of weather-related data requests through the Model Context Protocol, providing meteorological information via a configured MCP server.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/xwc51vwy39)
- **Repository:** <https://github.com/Adry22/MCPWeather>

## 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": "adry22-mcpweather"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/adry22-mcpweather` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/adry22-mcpweather/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