"Weather Inquiry" matching MCP servers:

Provides weather data, analysis, and report saving through MCP tools, with a Next.js chat interface.

Provides real-time weather alerts from the National Weather Service, news search capabilities via NewsAPI, and safe local directory exploration for AI assistants.

A demonstration MCP server created for learning purposes, allowing Claude AI to interact with local files and a Postgres database while implementing a custom Model Context Protocol.

Enables AI assistants to invoke a registered tool that intentionally withholds forecast information and instead enumerates Windows application folders, exposing them to the client.

Enables weather data retrieval and analysis through an MCP server interface with support for local file operations.

A demonstration MCP server showcasing tools (calculator, file operations, weather, timestamp), resources (server config, system info, documentation), and reusable prompt templates for code review, documentation, and debugging.

Model Context Protocol (MCP) server implementation demonstrating production-ready patterns in TypeScript, with tools for calculation, weather, and filesystem access.

Enables to perform mathematical calculations, retrieve weather information, and manage files through a standardized MCP interface, showcasing best practices for building MCP servers.

Enables a voice-enabled AI assistant to call 7 built-in MCP tools including calculator, web search (DuckDuckGo), weather (wttr.in), date/time, and local file read/write/list operations, integrating with Gemini 2.0 Flash for tool-calling conversations.

A proof-of-concept MCP server that enables LLMs to read local text files and fetch real-time weather data through external tools.

Exposes system tools (disk usage, file listing) and weather information via Open-Meteo to MCP-compatible LLMs.

Enables Claude to save, list, and read notes in a '/dev-notes' directory, and fetch live weather for any city using the wttr.in API.

An advanced Model Context Protocol server that integrates real-time weather data, local file system navigation, and geographic information with AI-powered analysis tools. It enables users to perform complex data evaluations and manage files while accessing live climatic and demographic data through compatible MCP clients.

Provides weather data via OpenWeatherMap API, file operations, and integration with remote PostgreSQL database for managing accrual records through a FastAPI backend, all accessible through natural language via Deepseek.

Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.

A minimal MCP server demo written without the MCP Python SDK that demonstrates the complete protocol flow. It provides weather, file search, and datetime tools, and includes a CLI client that bridges MCP tools with OpenAI function calling.

A beginner-friendly MCP server built in plain Node.js/JavaScript that exposes five tools (calculator, UUID generator, read notes, get weather, password generator) to teach how the Model Context Protocol works under the hood.

Enables AI models to access external services including weather data, file system operations, and SQLite database interactions through a standardized JSON-RPC interface. Features production-ready architecture with security, rate limiting, and comprehensive error handling.

Enables Claude to query a local SQLite database read-only, search and read files within a sandboxed directory, and get current weather and forecasts via Open-Meteo, all through natural language.

Enables an AI assistant to invoke local file operations, multi-engine web search, weather, system commands, developer utilities, and code execution over MCP, and includes a web dashboard for managing endpoints, testing tools, and viewing live logs.