# weather-mcp

> Use this tool when you need to access and utilize weather data from the Open-Meteo API, solving problems related to weather-based decision-making and data integration. It provides a decorator-driven interface with Zod schemas, accepting location-based inputs and outputting current and forecasted weather conditions via stdio and HTTP transports. Ideal for use cases requiring reliable and standardized weather data, such as climate monitoring, logistics, and outdoor activity planning.

Canonical page: https://skillsregistry.net/skills/ninemindai-agentback-demo  
JSON: https://api.skillsregistry.net/v1/skills/ninemindai-agentback-demo

## Description

Exposes weather data from the free Open-Meteo API via decorator-driven MCP tools with Zod schemas, supporting stdio and HTTP transports.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ecm8w1q1aw)
- **Repository:** <https://github.com/ninemindai/agentback-demo>

## 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": "ninemindai-agentback-demo"
    }
  }
}
```

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