# MCP-SERVER

> MCP-SERVER — dhruv610ag-mcp-server. Use this tool when you need to integrate Large Language Models (LLMs) with real-time weather data, enabling applications such as weather-aware chatbots or climate-informed text generation. The MCP-SERVER provides a lightweight Python implementation of the Model Context Protocol (MCP) to facilitate this connection. It accepts LLM queries as input and returns relevant weather data as output, making it ideal for use cases requiring dynamic and informed language model responses.

Canonical page: https://skillsregistry.net/skills/dhruv610ag-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/dhruv610ag-mcp-server

## Description

A lightweight Model Context Protocol (MCP) server in Python that connects Large Language Models (LLMs) to real-time weather data.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Dhruv610ag/MCP-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": "dhruv610ag-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dhruv610ag-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dhruv610ag-mcp-server/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