open-meteo-mcp vs python-sdk
open-meteo-mcp: Open-Meteo MCP Server is a comprehensive tool that integrates Open-Meteo weather APIs with Large Language Models, enabling AI assistants to access a wide range of meteorological data. It supports various weather models, historical data, air quality, and advanced forecasts, deployable via npm or Docker.; python-sdk: The MCP Python SDK provides a robust implementation of the Model Context Protocol, enabling developers to build secure, standardized servers that expose data and functionality to LLM applications. It also includes a client library for connecting to any MCP server, supporting various standard transports like stdio, Streamable HTTP, and SSE.
TL;DR
Retrieving current or future weather forecasts for any location.
- You want the official, MIT-licensed reference Python SDK maintained directly by the Model Context Protocol project.
- You need full low-level control over MCP primitives (resources, prompts, tools, sampling) and standard transports (stdio, SSE, Streamable HTTP).
- You want higher-level conveniences like automatic client composition or less decorator boilerplate; FastMCP wraps the protocol with extra ergonomics.
- You are exposing an existing GraphQL or FastAPI backend where a gateway or adapter (Grafbase or FastAPI-MCP) requires no manual tool code.
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