AccessibilityAI

AccessibilityAI

Autonomous WCAG 2.1 accessibility auditor that scans, fixes, re-verifies, and generates VPAT 2.5 EN 301 549 reports using AI vision analysis + DOM scanning.

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AccessibilityAI — by GroundLogic AI

Autonomous WCAG 2.1 accessibility auditor that scans, fixes, re-verifies, and generates VPAT 2.5 EN 301 549 reports using AI vision analysis + DOM scanning.

[Add demo GIF here]

License: MIT MCP Compatible WCAG 2.1


What It Does

AccessibilityAI is an open-source MCP server that:

  1. Scans a URL using axe-core (DOM) + Claude Vision (AI screenshot analysis)
  2. Generates surgical, framework-specific code fixes for every violation
  3. Re-verifies by re-scanning after fixes are applied, showing exactly what was resolved
  4. Produces a complete VPAT 2.5 EN 301 549 accessibility conformance report (all clauses, PDF + JSON)

It runs as an MCP server over Streamable HTTP — compatible with Claude Desktop, Claude Code, Cursor, and any MCP client.


Quick Start

This is a pnpm monorepo. The MCP server lives in artifacts/api-server/.

# 1. Clone and install
git clone https://github.com/groundlogic-ai-source/accessibility-ai
cd accessibility-ai
pnpm install

# 2. Install the Playwright browser (required for scanning)
npx playwright install chromium

# 3. Set environment variables
export DATABASE_URL="postgresql://user:pass@localhost:5432/accessibilityai"
# Or copy from a .env file — pnpm-workspace reads it automatically

# 4. Push the database schema
pnpm --filter @workspace/db run push

# 5. Start the MCP server
pnpm --filter @workspace/api-server run dev
# MCP endpoint:   http://localhost:8080/mcp
# Health check:   http://localhost:8080/api/healthz
# REST scan:      http://localhost:8080/api/scan  (no MCP client needed)

Bring Your Own Key

AccessibilityAI uses a Bring Your Own Key (BYOK) model. You supply your own Anthropic API key with each tool call — it is never stored, never logged, and used only for the duration of that single request.

Your key is never retained. See PRIVACY.md for full details.

You can get an Anthropic API key at console.anthropic.com.


MCP Tools

scan_accessibility

Scans a URL for WCAG 2.1 accessibility violations using DOM analysis and visual AI.

Input:

{
  "url": "https://example.com",
  "anthropic_api_key": "sk-ant-...",
  "scan_depth": "single_page",
  "max_pages": 1
}

Output:

{
  "scan_id": "uuid",
  "url": "https://example.com",
  "total_violations": 12,
  "violations_by_severity": { "critical": 2, "serious": 4, "moderate": 5, "minor": 1 },
  "estimated_fix_time": "2-4 hours",
  "violations": [...]
}

generate_fixes

Takes scan results and generates specific code fixes for each violation. Returns patches ready to paste into Claude Code or Replit Agent.

Input:

{
  "scan_id": "uuid-from-scan",
  "framework": "react",
  "anthropic_api_key": "sk-ant-..."
}

Output:

{
  "scan_id": "uuid",
  "fixes": [
    {
      "wcag_criterion": "1.1.1",
      "issue": "Image missing alt text",
      "before": "<img src=\"hero.jpg\">",
      "after": "<img src=\"hero.jpg\" alt=\"Hero banner showing product dashboard\">",
      "explanation": "...",
      "caveats": "..."
    }
  ],
  "copy_paste_summary": "Please fix the following accessibility violations in my codebase:\n..."
}

The copy_paste_summary field is formatted to paste directly into Claude Code or Replit Agent.


re_verify

Re-scans the URL after fixes have been applied and compares against the original scan.

Input:

{
  "scan_id": "original-scan-uuid",
  "anthropic_api_key": "sk-ant-..."
}

Output:

{
  "original_violations": 12,
  "current_violations": 3,
  "resolved": [...],
  "persisting": [...],
  "new_violations": [],
  "improvement_percentage": 75,
  "summary": "9 of 12 violations resolved (75% improvement). 3 violation(s) remain."
}

generate_vpat

Generates a complete VPAT 2.5 EN 301 549 accessibility conformance report. Returns a PDF (base64) and structured JSON covering all clauses.

Input:

{
  "scan_id": "uuid-from-scan",
  "product_name": "My SaaS App",
  "product_version": "2.1.0",
  "company_name": "Acme Corp",
  "contact_email": "accessibility@acme.com",
  "anthropic_api_key": "sk-ant-..."
}

Output:

  • vpat_json — Full structured VPAT report (all EN 301 549 clauses)
  • pdf_base64 — Base64-encoded PDF, decode and save as .pdf
  • overall_conformance_percentage — % of WCAG 2.1 Level A & AA criteria met

Used in Production

AccessibilityAI powers accessibility compliance workflows in healthcare and government sectors where VPAT documentation is required for procurement. Organizations use it to generate baseline conformance reports before manual audits, saving 4-8 hours per audit cycle.


Limitations

  • Automated tools detect approximately 40–60% of accessibility issues. Manual review by a certified accessibility specialist is recommended for full compliance certification.
  • VPAT reports generated by this tool should be reviewed before regulatory submission.
  • Full-site scans are capped at 10 pages. Deep navigation paths may not be reached.
  • Non-web EN 301 549 clauses (hardware, voice, closed software) are marked "Not Evaluated" — manual assessment required for those.
  • Scan results are retained for 1 hour. Re-run scan_accessibility if results expire.

MCP Client Configuration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "accessibility-ai": {
      "url": "https://your-deployed-instance.com/mcp",
      "transport": "streamable-http"
    }
  }
}

Claude Code / CLI

claude mcp add --transport http accessibility-ai https://your-deployed-instance.com/mcp

Contributing

Contributions are welcome. Please:

  1. Fork the repo and create a feature branch
  2. Follow existing code style (TypeScript strict mode, no any)
  3. Add or update tests for changed behavior
  4. Open a pull request with a clear description

For bug reports and feature requests, open a GitHub Issue.


License

MIT — see LICENSE for details.

GroundLogic AI — info@groundlogic.ai

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