MediaWiki MCP Server – Bridging AI and the World’s Largest Knowledge Base

The MediaWiki MCP Server solves a common pain point for developers building AI‑powered assistants: accessing structured, up‑to‑date information from Wikipedia and other MediaWiki‑based wikis without writing custom API wrappers. By exposing the MediaWiki REST API through the Model Context Protocol, it turns any wiki into a first‑class tool that an LLM can query, search, and retrieve content from in real time. This eliminates the need for separate authentication flows or data‑crawling pipelines, allowing developers to focus on higher‑level application logic.

At its core, the server offers two intuitive capabilities. The Search tool lets an assistant perform keyword‑based queries against any MediaWiki site, returning a configurable list of relevant page titles. The Get Page tool then fetches the full content of a specified page, providing structured JSON that can be rendered or parsed by downstream components. These operations are powered directly by the MediaWiki REST API, ensuring that results reflect the latest edits and maintain consistency with Wikipedia’s own data structures.

Key features include:

• Site agnosticism – By default the server targets , but any MediaWiki site can be used by simply supplying its base URL. The server automatically detects whether a suffix is required.
• Transport flexibility – It supports standard I/O, streamable HTTP, and Server‑Sent Events (SSE), allowing seamless integration into diverse deployment environments.
• Configurable limits – Search results can be capped, and page retrieval is precise to a title, preventing accidental over‑fetching.
• Minimal footprint – Written in Python 3.13 and built with , the server is lightweight, making it suitable for local prototypes or cloud‑based microservices.

Real‑world scenarios abound. An educational chatbot can answer student queries by searching for relevant Wikipedia pages and summarizing them on demand. A news aggregator might pull the latest coverage from a specialized wiki to provide context for trending topics. Even internal knowledge bases hosted on MediaWiki can be exposed to corporate LLMs, enabling employees to query policy documents or project documentation without leaving their conversational interface.

Because the server speaks MCP, it plugs straight into any client that understands the protocol—be it Claude, OpenAI’s GPT models, or custom LLM wrappers. Developers can declare the server in a JSON configuration and let the AI orchestrate calls to search or fetch pages as part of its reasoning process. This tight coupling reduces latency, removes the need for custom SDKs, and keeps data access declarative within the model’s prompts.

In summary, the MediaWiki MCP Server turns Wikipedia and any MediaWiki site into a low‑overhead, AI‑friendly data source. Its straightforward tools, flexible transport options, and zero‑code integration make it an indispensable component for developers who want to enrich conversational agents with authoritative, real‑time knowledge.