Accessibility Ai

io.github.groundlogic-ai-sourcePublished by GitHub account groundlogic-ai-sourcev1.0.0Updated Oct 24, 2026

Scan URLs for WCAG 2.1 violations, generate AI fixes, and produce VPAT 2.5 compliance reports.

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Overview

AI-generated overview

An MCP server that scans web pages for WCAG 2.1 accessibility violations, drafts code fixes, re-verifies them, and generates VPAT 2.5 conformance reports.

What you can do
Scan a URL for WCAG 2.1 violations using DOM analysis and AI screenshot review, with severity counts and estimated fix time, for a single page or up to 10 pages per site scan. Generate framework-specific code fixes for each violation, with before/after snippets and a paste-ready summary. Re-scan a URL after fixes and compare against the original scan to show resolved, persisting and new issues. Produce a VPAT 2.5 EN 301 549 conformance report as structured JSON and a base64 PDF.
When to use it
Useful when you need a quick accessibility baseline for a web page or small site, want draft code fixes for common WCAG issues, or need a starting VPAT document for procurement before a manual audit.
Requirements
A remote Streamable HTTP endpoint, or a self-hosted deployment from the pnpm monorepo with Node.js, pnpm, a Playwright Chromium browser and a PostgreSQL database via DATABASE_URL. Each tool call requires your own Anthropic API key, passed as the anthropic_api_key argument.
Before you install
The server is an early-stage beta and automated checks catch only about 40–60% of issues, so reports need review by a certified specialist before formal compliance use. Your Anthropic API key is sent with every tool call and billed to your account. Scans fetch the target URLs from the server, and scan results are retained for only 1 hour.

Installation

In SourceWeft

  1. Open Accessibility Ai in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.groundlogic-ai-source%2Faccessibility-ai/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "accessibility-ai": {
      "type": "http",
      "url": "https://accessibility.groundlogic.ai/mcp"
    }
  }
}

README

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.

⚠️ Beta Release — AccessibilityAI is an early-stage prototype. Automated tools detect approximately 40–60% of accessibility issues. Manual review by a certified specialist is recommended before submitting VPAT reports for formal compliance purposes. Expect rough edges — please share feedback or report bugs using the form below.

[Add demo GIF here]

[License: MIT] [MCP Compatible] [WCAG 2.1]


Feedback

AccessibilityAI is actively developed. If something breaks or you have a feature request, we want to know.

→ Open the feedback form

You can also open a GitHub Issue for bug reports.


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/.

bash
# 1. Clone and installgit clone https://github.com/groundlogic-ai-source/accessibility-aicd accessibility-aipnpm install
# 2. Install the Playwright browser (required for scanning)npx playwright install chromium
# 3. Set environment variablesexport DATABASE_URL="postgresql://user:pass@localhost:5432/accessibilityai"# Or copy from a .env file — pnpm-workspace reads it automatically
# 4. Push the database schemapnpm --filter @workspace/db run push
# 5. Start the MCP serverpnpm --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:

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

Output:

json
{  "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:

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

Output:

json
{  "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:

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

Output:

json
{  "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:

json
{  "scan_id": "uuid-from-scan",  "product_name": "My SaaS App",  "product_version": "2.1.0",  "company_name": "Acme Corp",  "contact_email": "[email protected]",  "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

Example Prompts

Use these prompts with Claude Desktop, Claude Code, or any MCP client connected to AccessibilityAI:

1. Scan a site and get a violation summary:

Scan https://example.com for WCAG 2.1 accessibility violations using my Anthropic key sk-ant-... and give me a prioritized summary of what needs to be fixed.

2. Generate code fixes for a specific framework:

Use the scan_id from the accessibility scan you just ran to generate React code fixes for all the violations. Format them so I can paste them directly into my codebase.

3. Re-verify fixes and produce a VPAT report:

Re-verify https://example.com using the original scan_id to confirm my fixes resolved the issues, then generate a complete VPAT 2.5 compliance report for "Acme Corp" and return the PDF.

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:

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

Claude Code / CLI

bash
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 or use the feedback form.


License

MIT — see LICENSE for details.

GroundLogic AI — [email protected]

Source: README.md at commit 8640b9b

Tools

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Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

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