# Weather

> Use this tool when you need to integrate real-time weather information into AI assistants, enabling them to provide location-specific updates, plan outdoor activities, or analyze climate patterns. It solves problems such as accessing current conditions, forecasts, and other meteorological data, and provides a streamlined interface for efficient HTTP requests. It is ideal for applications requiring up-to-date weather information, such as travel planning or climate analysis, and accepts location inputs to output relevant weather data.

Canonical page: https://skillsregistry.net/skills/sunwood-ai-labs-weather  
JSON: https://api.skillsregistry.net/v1/skills/sunwood-ai-labs-weather

## Description

This weather service MCP server, developed for integrating weather data into AI assistants, provides a streamlined interface for accessing real-time weather information. It utilizes the httpx library for efficient HTTP requests and integrates with external weather APIs to fetch current conditions, forecasts, and other meteorological data. The server's modular structure, defined in the pyproject.toml, allows for easy deployment and scalability. By connecting AI capabilities with weather data, this implementation enables assistants to provide location-specific weather updates, plan outdoor activities, or analyze climate patterns. It is particularly useful for applications requiring up-to-date weather information, travel planning, or any scenario where an AI system needs to reason about and respond to current and forecasted weather conditions.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/sunwood-ai-labs-weather)
- **Repository:** <https://github.com/sunwood-ai-labs/mcp-weather-service-server>

## 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": "sunwood-ai-labs-weather"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sunwood-ai-labs-weather` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sunwood-ai-labs-weather/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