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Wikipedia MCP Server
for AI Agents

Connect your AI agent to StackOne's Wikipedia MCP server and give it ready-to-use MCP tools out of the box. Auth, tool execution, and security all managed.

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Wikipedia MCP Server
Built by StackOne StackOne
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Coverage

15 Agent Actions

Create, read, update, and delete across Wikipedia — and extend your agent's capabilities with custom actions.

MCP Actions → Build Actions →

Authentication

Agent Tool Authentication

Per-user OAuth in one call. Your Wikipedia MCP server gets session-scoped tokens with zero credentials stored on your infra.

Agent Auth →

Security

Agent Protection

Every Wikipedia tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.

Prompt Injection Defense →

Performance

Max Agent Context. Min Cost.

Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Wikipedia call.

Tools Discovery →

What is the Wikipedia MCP Server?

A Wikipedia MCP server lets AI agents read and write Wikipedia data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Wikipedia MCP server ships with pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.

All Wikipedia MCP Tools

Every action from Wikipedia's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.

Featured Contents

  • Get Featured Content

    Get the featured Wikipedia content for a given date.

On This Days

  • Get On This Day

    Get historical events that happened on a given day.

Files

  • Get File

    Get information about a file, including download links.

Pages

  • Create Page

    Create a new wiki page.

  • Get Page

    Get a wiki page's wikitext source and metadata.

  • Search Pages

    Search Wikipedia page titles and contents for the provided terms.

  • Update Page

    Update an existing wiki page.

Page Metadatas

  • Get Page Metadata

    Get a wiki page's metadata without its content.

Page With HTMLs

  • Get Page With HTML

    Get a wiki page's metadata plus its latest content rendered as HTML.

Page Language Links

  • Get Page Language Links

    Get pages on the same topic in other languages.

Page Media Files

  • Get Page Media Files

    Get the media files used on a wiki page.

Page Historys

  • Get Page History

    Get the latest revisions to a wiki page.

Page History Counts

  • Get Page History Counts

    Get aggregated edit statistics for a wiki page.

Revisions

  • Get Revision

    Get details for an individual revision by its revision ID.

Titles

  • Search Titles

    Search page titles for prefix (typeahead) matches.

Set Up Your Wikipedia MCP Server in Minutes

One endpoint. Any framework. Your agent is talking to Wikipedia in under 10 lines of code.

MCP Clients

Claude Desktop setup guide
Claude Code setup guide
Cursor setup guide
Goose setup guide

Agent Frameworks

Claude Desktop
{
  "mcpServers": {
    "stackone": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "https://api.stackone.com/mcp?x-account-id=<account_id>",
        "--header",
        "Authorization: Basic <YOUR_BASE64_TOKEN>"
      ]
    }
  }
}

Check More Documents & Knowledge MCP Servers

Confluence

134+ actions

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101+ actions

NinjaOne

96+ actions

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95+ actions

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92+ actions

Contentful

80+ actions

Google Shopping

80+ actions

All Documents & Knowledge MCP Servers →

Platform Resources

MCP Code Mode: Keeping Tool Responses Out of Agent Context

Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.

11 min

Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery

Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.

10 min

Indirect Prompt Injection Defense for MCP Tools: A Technical Guide

MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.

12 min

MCP vs A2A: Architecture, Security, and When to Use Each

MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.

12 min

MCP vs API: What 200+ Connector Builds Taught Us

MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.

14 min read

Wikipedia MCP Server FAQ

Does StackOne have a Wikipedia MCP server?
Yes. StackOne offers a hosted Wikipedia MCP server, and every action is tested and QA'd by StackOne. Connect it to Claude, Cursor, and any other MCP client, or to any agent framework through the AI Action SDK. It ships with managed agent authentication, prompt injection defense, and tool discovery with server-side execution that preserve your agent's context window and keep reasoning performance.
Wikipedia MCP server vs direct API integration — what's the difference?
A Wikipedia MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling Wikipedia. A Wikipedia MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling Wikipedia at runtime. StackOne provides both.
How does Wikipedia authentication work for AI agents?
Wikipedia authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own Wikipedia account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via origin_owner_id.
Are Wikipedia MCP tools vulnerable to prompt injection?
Yes — Wikipedia MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a Wikipedia agent and how do I avoid it?
Context bloat happens when Wikipedia tool schemas and API responses eat your Wikipedia agent's memory, preventing it from reasoning effectively. A single Wikipedia query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my Wikipedia agent can access?
Yes — you can limit which actions your Wikipedia agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my Wikipedia MCP server?
Yes — you can create custom agent actions for your Wikipedia MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research Wikipedia's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a Wikipedia MCP server?
Skip a Wikipedia MCP server if your integration is purely software-to-software — direct Wikipedia API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call Wikipedia actions at runtime.
What AI frameworks and AI clients does the StackOne Wikipedia MCP server support?
The StackOne Wikipedia MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.

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All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.

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