"A source for finding weather information" matching MCP servers:

MCP server for searching, browsing, and analyzing decompiled Minecraft source code locally. Supports symbol lookup, text search, reference lookup, and lightweight RAG.

Enables a local, read-only search over user-provided tabletop campaign source cards and module directories, routing queries to ranked hits across Markdown, JSON, and YAML text files while excluding core rulebook and SRD content by default. Returns file-and-line pointers with small context windows, plus explicit private-source opt-in, so a game master can locate and open the exact passage in their own library.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Enables AI coding agents to search and read local Markdown knowledge bases generated by Agent Docs for Markdown, across single or multiple workspaces, including link/backlink discovery and index status checks.

Provides weather intelligence as MCP tools (current weather, forecast, air quality, UV index, alerts) with agentic orchestration, memory, and citation-grounded RAG.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables users to get real-time weather data and contextual natural-language insights for any city by combining OpenWeather API with a RAG pipeline and Groq LLM, and can be used via MCP clients like GitHub Copilot.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Enables fetching weather forecasts for Israeli cities by controlling a headless browser via Playwright, instead of using a conventional weather API.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Enables AI assistants to perform intent routing, retrieval reranking, and batch semantic judgments on Cloudflare Workers, returning structured answers with confidence scores instead of generated prose.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

A demonstration project for Model Context Protocol (MCP) that integrates weather services with multiple AI models (Claude, GPT, Gemini), enabling natural language queries for weather alerts and forecasts.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.