Wikipedia
An MCP server project that provides the function of accessing Wikipedia pages.
2.5 points
9.0K

What is the MCP Wikipedia Server?

The MCP Wikipedia Server allows you to quickly access articles on Wikipedia through simple commands. It is a lightweight tool designed to simplify the information retrieval process.

How to use the MCP Wikipedia Server?

Simply start the server and enter keywords to get the corresponding Wikipedia content.

Applicable Scenarios

Suitable for users who need to quickly find knowledge, research topics, or for daily learning.

Main Features

Support for multiple keyword queries
Users can directly obtain relevant Wikipedia pages by entering keywords.
Real-time updates
Based on the latest version of the Wikipedia database to ensure the timeliness and accuracy of information.
Advantages
Simple operation, no complex configuration required
Cross - platform support, compatible with Windows, Linux, and MacOS
Limitations
Interrupted network connection may affect normal use
Some content may be restricted due to copyright issues

How to Use

Install the dependency environment
Ensure that the Python and Node.js environments are installed.
Start the server
Run the provided startup script to initialize the server.
Send a query request
Enter keywords in the client to search.

Usage Examples

Case 1: Query for 'Artificial Intelligence'
The user enters the keyword 'Artificial Intelligence', and the server returns the corresponding Wikipedia page.
Case 2: Search for 'Quantum Physics'
The user enters the keyword 'Quantum Physics', and the server returns the Wikipedia page about quantum physics.

Frequently Asked Questions

What should I do if the server fails to start?
What should I do if I can't find some entries?

Related Resources

Project GitHub Repository
Get more documentation and support.
Wikipedia Official Website
Learn more about Wikipedia.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "wikipedia": {
      "command": "uv",
      "args": [
        "--directory",
        "%USERPROFILE%/Documents/GitHub/mcp-wikipedia",
        "run",
        "python",
        "main.py"
      ]
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

M
MCP
The Microsoft official MCP server provides search and access functions for the latest Microsoft technical documentation for AI assistants
10.0K
5 points
S
Shadcn Ui MCP Server
An MCP server that provides shadcn/ui component integration for AI workflows, supporting React, Svelte, and Vue frameworks. It includes functions for accessing component source code, examples, and metadata.
TypeScript
12.2K
5 points
A
Annas MCP
The MCP server and CLI tool of Anna's Archive are used to search for and download documents on the platform and support access through an API key.
Go
5.7K
4.5 points
S
Search1api
The Search1API MCP Server is a server based on the Model Context Protocol (MCP), providing search and crawling functions, and supporting multiple search services and tools.
TypeScript
14.6K
4 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
45.0K
4.3 points
B
Bing Search MCP
An MCP server for integrating Microsoft Bing Search API, supporting web page, news, and image search functions, providing network search capabilities for AI assistants.
Python
15.2K
4 points
M
Modelcontextprotocol
Certified
This project is an implementation of an MCP server integrated with the Sonar API, providing real-time web search capabilities for Claude. It includes guides on system architecture, tool configuration, Docker deployment, and multi-platform integration.
TypeScript
13.6K
5 points
B
Bilibili MCP Js
Certified
A Bilibili video search server based on the Model Context Protocol (MCP), providing API interfaces to support video content search, paginated queries, and video information return, including LangChain call examples and test scripts.
TypeScript
15.6K
4.2 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
16.6K
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
14.8K
4.5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
23.6K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
45.0K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
19.2K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
44.5K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
30.3K
4.8 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
62.9K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2025AIBase