wikipedia-mcp: A Model Context Protocol (MCP) server that retrieves information from Wikipedia to provide context to LLMs

by Rudra-ravi · MCP Server · ★ 295

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install wikipedia-mcp

pipx install wikipedia-mcp
npx -y @smithery/cli install @Rudra-ravi/wikipedia-mcp --client claude

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 80/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

anthropicllmmcp-serveropen-sourcewikipediawikipedia-apiwikipedia-mcpwikipedia-mcp-server

Quick Facts

Stars295
Forks58
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score80/100
Open Issues3
Last Updated2026-05-01
Created2025-03-08
Platformsmcp, python
Est. Tokens~22k

About wikipedia-mcp

Wikipedia MCP Server A Model Context Protocol (MCP) server that retrieves information from Wikipedia to provide context to Large Language Models (LLMs). This tool helps AI assistants access factual information from Wikipedia to ground their responses in reliable sources.

Compatible Skills

These tools work well together with wikipedia-mcp for enhanced workflows:

  • STORM-Research-Assistant — semantic(0.34)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • llm-tools-kiwix — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (55%)

wikipedia-mcp alternative? Top 6 similar tools

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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