# Agentic MCP Weather System

> Use this tool when you need to access intelligent weather services with natural language queries and forecasting capabilities. It solves problems related to weather monitoring and alert systems, providing outputs such as forecast data and alert notifications through a Docker-supported multi-server architecture. Ideal for use in applications requiring local language model integration and real-time weather information.

Canonical page: https://skillsregistry.net/skills/shivbaj-mcp  
JSON: https://api.skillsregistry.net/v1/skills/shivbaj-mcp

## Description

Provides intelligent weather services through an orchestrated multi-server architecture with Docker support, enabling natural language weather queries, forecasting, and alert monitoring powered by local LLM integration.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qr2atdh17g)
- **Repository:** <https://github.com/Shivbaj/MCP>

## 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": "shivbaj-mcp"
    }
  }
}
```

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