"Wikipedia" matching MCP servers:

An MCP server that gives LLMs access to Wikipedia, supporting search, article retrieval, summaries, sections, and related topics across multiple languages and language variants.

Enables AI agents to search, read, and explore Wikipedia articles via tools like summaries, categories, and random articles, with no API keys required.

A Model Context Protocol server that retrieves information from Wikipedia to provide context to LLMs, allowing users to search articles, get summaries, full content, sections, and links from Wikipedia.

Provides offline search and retrieval of Wikipedia articles using Kiwix .zim files, enabling LLMs to access full Wikipedia content without internet.

Enables searching and retrieving Wikipedia content across multiple languages, including article summaries, sections, coordinates, and related topics.

A conversational AI server that enables users to search Wikipedia and retrieve information through natural language interactions using LangGraph and Model Context Protocol (MCP).

A Model Context Protocol server that enhances LLM capabilities by connecting to Wikipedia, internet search (Tavily), and financial data (Yahoo Finance) tools, enabling contextual responses to user queries.

Enables offline CRUD and semantic search on Wikipedia ZIM archives via MCP tools for reading, writing, editing, deleting, and searching articles.

Enables AI models to retrieve high-quality context from Valyu's API, including search over Wikipedia, arXiv papers, and the web.

Structured knowledge for AI agents — Wikipedia, Wikidata, Wiktionary and growing as clean JSON. 1.9M searchable. Free, no auth.

Enables completely offline Wikipedia search through locally-indexed content using BM25 algorithm, allowing AI assistants to query Wikipedia without internet connectivity or external API calls.

Enables hybrid search (dense + sparse) over self-hosted indexes of continuously ingested public datasets (news, GitHub, Wikipedia, arXiv, small web, devdocs, Hacker News) using your own embedding model, served via the Model Context Protocol.

Enables document Q&A, summarization, keyword extraction, and Wikipedia lookup through MCP tools, using RAG with FAISS and Ollama.

Enables agents to search and retrieve clean, structured content from local offline ZIM archives such as Wikipedia, medical docs, DevDocs, and Stack Exchange through a unified MCP interface.

AI-powered deep research agent with multi-source search (DuckDuckGo, Google News, Reddit, Wikipedia), structured analysis (SWOT, comparisons, timelines, Google Trends), financial data with charts, and PDF report generation. 11 MCP tools. Multi-LLM support (DeepSeek, Gemini, GLM, OpenAI).