"Wikipedia" matching MCP servers:

MCP server providing free, IP-direct tools for web search, crawling, anti-detect browsing, and structured data from Wikipedia, Wikidata, GitHub, and YouTube.

Enables web search through Google and Wikipedia plus content extraction from any webpage via the Seekr API. Provides real-time search results with advanced filtering options and clean text extraction capabilities.

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.

An MCP server that enables web searching, URL content extraction, and summarization without requiring API keys. It also provides advanced mathematical evaluation and multi-language Wikipedia summary retrieval tools.

A MCP server that fetches and renders Baidu Baike (Chinese Wikipedia) discussion content, allowing users to access encyclopedia article discussions and generate readable analysis of the structured data.

Enables LLMs to research answers using DuckDuckGo web and news search plus Wikipedia, providing up-to-date information and current events.

Enables local LLMs to search the web, scrape pages, and extract structured data (tables, metadata) from sources like Wikipedia and IMDb, with caching and rate limiting.

Provides web search and content retrieval optimized for AI coding assistants, returning full conversations and structured content from StackOverflow, GitHub Issues, arXiv, and Wikipedia in a single call.

Enables parallel fan-out across many search engines and vertical sources, with consensus-merge deduplication, local cross-encoder reranking, and cited Groq-synthesized answers. Also fetches and converts pages, PDFs, and documents to markdown, drives a real browser for interaction, extracts structured JSON, surveys site maps, and queries Wikipedia and arXiv directly.

Exposes every installed .act.yaml blueprint as a deterministic MCP tool, letting AI agents fetch structured data or perform actions from websites and portals via a tiered HTTP, HTML-extraction, and headless-browser fallback chain. This replaces slow, costly browser automation with fast, verifiable tool calls for sources like GitHub, Hacker News, Wikipedia, PyPI, and weather or exchange-rate services.

Enables multi-engine parallel search with cross-validation, combining Brave, Tavily, DuckDuckGo, Wikipedia, Bing, and Mojeek, and labeling results with confidence levels based on engine agreement.

Provides web search, URL fetching, summarization, math evaluation, and Wikipedia tools for LM Studio without needing an API key.

Enables AI agents to search the web, read any page as clean markdown, and query Wikipedia, Hacker News, and GitHub without API keys or per-call credits. It exposes these sources as unified MCP tools and can also be self-hosted over HTTP or used as a library.

Enables LibreChat assistants to browse and fetch web content only from an allowlisted set of domains, with the allowed origins made visible to the model. It runs as a streamable-HTTP Docker service that enforces domain restrictions and supports sites like GitHub, Wikipedia, and Google.

Enables debate search and citation functionality through web search, Wikipedia, arXiv, and AWS documentation APIs. Designed to power debate features with comprehensive research and citation tools via MCP protocol.

An MCP server that searches and scrapes multiple sources concurrently (web, DuckDuckGo, Wikipedia, arXiv, Hacker News) and renders an interactive picker UI where users can multi-select sources and delve into full page content.