"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.

This MCP server provides Wikipedia page view trend data, enabling AI to detect spikes, view historical traffic, and compare cross-platform trends to gauge public curiosity.

Enables efficient Wikipedia access through a progressive retrieval strategy that minimizes token usage by searching, summarizing, and fetching only relevant sections.

Enables LLMs to search for keywords and fetch full page content from Wikipedia across various languages. It provides direct access to Wikipedia information through search and fetch tools.

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.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Search across a billion+ documents including academic papers, books, code, legal cases, forums, and Wikipedia. Provides search and detail tools for various content types.

Local-first MCP server that captures web URLs (X, Reddit, YouTube, Wikipedia, articles) as typed data + Markdown into a self-hosted capture/store/recall substrate, with offline semantic recall. Six tools over a local khiipd daemon; run khiipd serve first.

An MCP server that enables interaction with Kiwix HTTP servers to browse, search, and retrieve content from offline ZIM books like Wikipedia. It provides tools for listing available library resources and fetching full-text articles as plain text.

An MCP server that provides offline access to ZIM file archives, including Wikipedia, medical knowledge, and maps. It dynamically exposes tools like search, article retrieval, and driving route planning based on available ZIM files.

Enables AI agents to search and fetch high-quality information from multiple sources, including general web APIs, Wikipedia, arXiv, Hacker News, Stack Exchange, and Crossref, with optional pro-mode deep research and clean markdown page extraction.

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).

An MCP server that turns an AI agent into a slide author, enabling drafting decks in Pandoc Markdown, compiling to PDF or PowerPoint, validating with PNG exports, and pulling in research from the web, Wikipedia, and Semantic Scholar.

An MCP server that enables LLMs to search, summarize, and retrieve detailed information from Wikipedia across multiple languages. It supports automated fact-checking by allowing models to proactively verify factual claims using Wikipedia's database.