Accessible code at the speed of AI

Model Context Protocol is an open standard that connects an AI agent to an outside source of data or expertise. An MCP server is what provides that source. AudioEye's SDK MCP, for example, is an MCP server that gives your coding agent access to AudioEye's accessibility data set.

Cursor, GitHub Copilot, and Claude Code, along with any IDE that supports Model Context Protocol. Developers keep working in the editor they already use.

The SDK finds accessibility issues; the MCP fixes them. The SDK is a testing tool that runs in your pipeline and reports what it detects, whether that’s a single component, a full page, or every deployment. AudioEye’s SDK MCP is a fixing tool that runs inside your AI coding agent, writing the correction and rescanning to confirm it worked. They solve different halves of the same problem.

Yes. Approval is what keeps you in control of your own codebase. The agent has already found the issue, written the correction, and confirmed it worked, so your developer is reading a finished change rather than researching one. They approve it and ship it through their normal process, which means the fix moves at the speed of any other code review.

No. The MCP uses automation to detect and fix issues in your code, and automation cannot catch every accessibility issue. Expert audits test with assistive technology and real users, which is how the high-impact issues get found. Most teams need both.

Not reliably. Most coding agents learned from a web that mostly isn't accessible, so unprompted they default to div buttons, unlabeled inputs, and missing alt text. They also can't see the rendered page, so anything that only appears at runtime, like focus order, contrast in context, or screen reader behavior, goes unnoticed.

Yes. AudioEye's MCP server connects your coding agent to real accessibility testing, so it can scan a page, pull back specific WCAG issues with the elements and success criteria involved, and return recommended fixes without leaving the IDE. You review and apply the changes.

An important note: no automated tool certifies compliance on its own. The MCP server handles the automated layer at the point of authoring. Expert testing handles what requires human judgment.

You’ll need an AudioEye account, Node 22 or 24, and a JavaScript or TypeScript project. From there, follow these steps:

Copy your Client ID and Client Token from the AudioEye Customer Portal

Configure your package manager to authenticate against AudioEye’s private registry, then export both credentials as environment variables.

Install the package: npm install -g @audioeye/testing-sdk-mcp

Register the server with your coding agent; Config differs by agent.

For a full setup, including CI/CD, see our developer docs.