How to Use the Accessibility Prover MCP in Vercel AI SDK

Run real-time WCAG 2.2 audits directly inside your streaming Vercel AI SDK interface before a single line of UI code renders.

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Connect Accessibility Prover MCP to Vercel AI SDK

Create your Vinkius account to connect Accessibility Prover to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Accessibility Prover with Vercel AI SDK

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Stop broken layouts before they stream to your Vercel AI SDK UI

When your Vercel AI SDK app streams UI components live, you can't afford to output inaccessible markup. The `validate_accessibility` tool intercepts the generation process to verify that your agent maps landmarks using semantic elements instead of cheap div click handlers. This ensures screen readers navigate the live-rendered output correctly from the very first frame. By embedding this MCP tool directly into your streaming loop, your agent runs checks in the background. It evaluates contrast ratios and keyboard focus paths on the fly. You get clean, accessible React or Next.js code streamed directly to your users without awkward loading spinners or post-render layout shifts.

Enforce contrast specs and keyboard traps on the Edge

Running on Vercel's edge network means every millisecond counts, and so does every line of CSS. Your agent uses `validate_accessibility` to calculate numerical contrast ratios like 4.5:1 and enforce strict keyboard tab orders before sending components to the client. The tool blocks execution if it finds a focus trap failure, forcing the agent to patch the design instantly. This tight integration means you don't ship broken UI to your edge routes. The agent automatically defines prefers-reduced-motion overrides and explicit form-label relationships in its generated payload. You get production-ready, fully compliant code on every single stream.

Strict EAA 2025 compliance for interactive components

Building for European accessibility standards requires absolute precision with interactive widgets. This MCP Server forces your agent to explicitly declare aria-labels and modal traps during the generation phase. If the `validate_accessibility` tool rejects the design, your agent has to fix the barriers before Vercel AI SDK ever outputs the code. You get a reliable safety net that runs directly in your TypeScript backend. No more shipping components that blind-side your QA team. Your agent learns to output compliant code because the validation step refuses to let bad markup pass through.

Setup guide

Set up Accessibility Prover MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Accessibility Prover tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Accessibility Prover transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Accessibility Prover. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Accessibility Prover MCP in Vercel AI SDK

It runs validation before the streaming payload starts rendering on the frontend. The `validate_accessibility` tool blocks the generation of raw HTML if semantic landmarks or ARIA labels are missing. This keeps your UI stable because the agent only streams compliant, fully-formed components.

Yes, this MCP Server works perfectly with Edge-compatible clients. You initialize the client in your API route, pass the tools to `streamText`, and let the agent validate the code on the fly. Just make sure to call the close method when the stream finishes.

Yes, when you connect the server to your Vercel AI SDK setup, validation errors stream directly into your development console. If the agent fails to hit the 4.5:1 contrast ratio, the tool rejects the design. Your agent immediately catches the failure and rewrites the CSS variables before the user sees the final UI.

Vinkius manages the MCP Server connection and handles the security side. You only need a single endpoint token in your environment variables. Pass this token when setting up the HTTP transport in your TypeScript code, and your agent gets instant access to the validation tools.

The server only processes the raw UI design specifications, HTML landmarks, and CSS overrides you send for validation. Your data runs inside an isolated, ephemeral V8 sandbox hosted by Vinkius. Nothing is stored long-term, and all validation tokens are scrubbed the moment the connection closes.

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