18 个#wikipedia MCP 服务器和客户端

Wikipedia MCP Server

Rudra-ravi

A Model Context Protocol (MCP) server that retrieves information from Wikipedia to provide context to LLMs.

MediaWiki MCP Server 🚀

shiquda

A MCP server that allows you to search and retrieve content on any wiki site using MediaWiki with LLMs 🤖 wikipedia.org, fandom.com, wiki.gg and more sites using Mediawiki are supported!

Wikipedia MCP Server

timjuenemann

Wikipedia MCP Server written in TypeScript

Wikipedia MCP Server

danbunnell

A simple MCP Server in Python for working with Wikipedia topic content in a GenAI context

A Model Context Protocol (MCP) server that provides access to Wikipedia content, prioritizing Simple English Wikipedia with intelligent fallback to regular English Wikipedia when content is unavailable or of poor quality.

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Wikimedia Image Search

yanexr

An MCP server enabling AI assistants or agents to search Wikimedia Commons images with metadata and visual thumbnails.

Better MCP wikipedia. algonacci's version cannot return page content properly.

Wikipedia Summarizer MCP Server

codingaslu

An MCP (Model Context Protocol) server that fetches and summarizes Wikipedia articles using Ollama LLMs, accessible via both command-line and Streamlit interfaces. Perfect for quickly extracting key information from Wikipedia without reading entire articles.

Trends MCP

trendsmcp

Real-time trend data from Google Trends (Search, Images, News, Shopping), YouTube, TikTok, Reddit, Amazon, Wikipedia, X (Twitter), LinkedIn, Spotify, GitHub, Steam, npm, App Store, news sentiment and web traffic via one MCP connection. Free API key, no credit card required.

Twosio

2s-io

575+ pay-per-call tools for AI agents: ground-truth data, AI gateway, and agent infra. x402 USDC, no keys, upto usage billing.

Wikipedia MCP Server

1999AZZAR

Minimal TypeScript-based HTTP server exposing Wikipedia search and page retrieval via MediaWiki API

MCP-Wikipedia-API-Server

Rishavv007

A FastAPI-MCP server that fetches Wikipedia summaries for AI assistants, deployed using Google Colab and Ngrok.