mcp-accessibility-scanner: An MCP (Model Context Protocol) server for performing accessibility audits on webpages using axe-core

by JustasMonkev · MCP Server · ★ 57

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

How to install mcp-accessibility-scanner

npm install -g mcp-accessibility-scanner
docker pull justasmonkev/mcp-accessibility-scanner

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 77/100

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. Full audit →

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.

accessbilityaimcp

Quick Facts

Stars57
Forks15
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score77/100
Open Issues7
Last Updated2026-10-21
Created2025-01-26
Platformsbrowser, mcp, node
Est. Tokens~17k

About mcp-accessibility-scanner

MCP Accessibility Scanner 🔍 A powerful Model Context Protocol (MCP) server that provides automated web accessibility scanning and browser automation using Playwright and Axe-core. This server enables LLMs to perform WCAG compliance checks, interact with web pages, manage persistent browser sessions, and generate detailed accessibility reports with visual annotations.

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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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