%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
MCP Wikipedia API Server
An MCP server based on FastAPI for obtaining Wikipedia summaries, supporting AI assistant interaction, and can be quickly deployed via Google Colab and Ngrok.
rating : 2 points
downloads : 9.7K
What is the MCP-Wikipedia-API-Server?
The MCP-Wikipedia-API-Server is a Model Context Protocol (MCP) server built on FastAPI, designed to help AI assistants quickly access brief information from Wikipedia. It can return relevant Wikipedia summaries based on user queries.How to use the MCP-Wikipedia-API-Server?
You can start the server and begin using it in just a few steps. First, deploy the server on Google Colab. Then, expose it to the public network via Ngrok. Finally, the AI assistant can call the API to obtain the required information.Use cases
It is suitable for scenarios that require rapid retrieval of Wikipedia knowledge, such as education, research, and content creation.Main features
Support for Wikipedia summary queries
Return the corresponding Wikipedia summary based on the keywords or questions provided by the user.
Built on FastAPI
Use the high-performance FastAPI framework to ensure fast and stable interface responses.
Integrated with Google Colab and Ngrok
No complex configuration is required. One-click deployment and public access are available.
Advantages
Easy to use and can be quickly deployed without complex settings.
Based on Wikipedia's powerful database, covering a wide range of knowledge.
Supports real-time queries to meet immediate needs.
Limitations
Depends on network connection and cannot operate offline.
Only supports English Wikipedia data, with limited multilingual support.
How to use
Install dependencies
Run the following command in Google Colab to install the required Python packages.
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%230080ff;%20}%20%3c/style%3e%3c/defs%3e%3cpath%20class='st0'%20d='M16.2,11.1c.4.5.4,1.2,0,1.8l-4.7,7.1h-3.8l5.3-8L7.6,4h3.8l4.7,7.1Z'/%3e%3c/svg%3e)
Configure Ngrok
Get your Ngrok authentication token and enter the command in Colab for configuration.
Start the server
Execute the script to start the MCP-Wikipedia-API-Server.
Usage examples
Query 'Artificial Intelligence'
The user enters the keyword 'Artificial Intelligence', and the server returns the Wikipedia summary about artificial intelligence.
Search for 'Quantum Mechanics'
The user enters the keyword 'Quantum Mechanics', and the server returns the Wikipedia summary about quantum mechanics.
Frequently Asked Questions
How can I ensure that my query request is successful?
Does it support multilingual queries?
Why can't I see any results?
Related resources
GitHub repository
View the source code and more documentation.
FastAPI official documentation
Learn more about FastAPI.
Ngrok official website
Get help and support for the Ngrok tool.
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
34.6K
5 points
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
20.5K
4.5 points
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
24.7K
4.3 points
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
72.7K
4.3 points
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#
32.6K
5 points
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
63.9K
4.5 points
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
22.1K
4.5 points
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
48.5K
4.8 points