# Model-Context-Protocol-MCP---Weather-Tool-Server-Agent-Interoperability

> Model-Context-Protocol-MCP---Weather-Tool-Server-Agent-Interoperability — nishnarudkar-model-context-protocol-mcp-weather-tool-server-agent-interoperability. Use this tool when you need to standardize communication between AI agents and external tools, enabling cross-framework interoperability. It solves problems of fragmented tool execution and agent logic, allowing for seamless integration of various tools and agents. The tool takes in AI agent requests and tool outputs, providing a standardized interface for interoperability between diverse systems.

Canonical page: https://skillsregistry.net/skills/nishnarudkar-model-context-protocol-mcp-weather-tool-server-agent-interoperability  
JSON: https://api.skillsregistry.net/v1/skills/nishnarudkar-model-context-protocol-mcp-weather-tool-server-agent-interoperability

## Description

An implementation of Anthropic's Model Context Protocol (MCP) using the Python MCP SDK. This repository demonstrates how to standardize communication between an AI agent and external tools, separating tool execution from agent logic for true cross-framework interoperability.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/nishnarudkar/Model-Context-Protocol-MCP---Weather-Tool-Server-Agent-Interoperability)

## 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": "nishnarudkar-model-context-protocol-mcp-weather-tool-server-agent-interoperability"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nishnarudkar-model-context-protocol-mcp-weather-tool-server-agent-interoperability` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nishnarudkar-model-context-protocol-mcp-weather-tool-server-agent-interoperability/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