# weather-mcp-server1

> Use this tool when you need to access and manage weather-related data, solving problems such as tracking climate conditions or forecasting future weather patterns. It provides an interface for inputting location or date parameters and outputting corresponding weather information. Utilize it in contexts where real-time or historical weather data is required, such as environmental monitoring or travel planning.

Canonical page: https://skillsregistry.net/skills/megg-ops-weather-mcp-server1  
JSON: https://api.skillsregistry.net/v1/skills/megg-ops-weather-mcp-server1

## Description

weather

## Trust

- **Trust score (0–1):** 0.75
- **Verification tier:** verified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** maps-location
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/megg-ops/weather-mcp-server1)
- **Repository:** <https://github.com/megg-ops/weather-mcp-server1>

## 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": "megg-ops-weather-mcp-server1"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/megg-ops-weather-mcp-server1` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/megg-ops-weather-mcp-server1/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