How to Use the Accessibility Checker MCP in Vercel AI SDK

See Accessibility Checker results live in your UI using the Vercel AI SDK.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Accessibility Checker MCP to Vercel AI SDK

Create your Vinkius account to connect Accessibility Checker to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Accessibility Checker with Vercel AI SDK

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Real-Time Compliance Checks with Vercel AI SDK

The `check_doorway` tool immediately verifies if an entry opening is wide enough for mobility aids. Because you're using the Vercel AI SDK, the compliance status streams directly into your React component; users see the data populate in real time without needing a loading spinner. This live feedback loop means developers can build highly interactive user experiences. You pass the results of `check_corridor_and_passage` right to the client-side UI for instant validation.

Streaming Results from the Accessibility Checker

When you run a full structural analysis, the MCP Server streams every finding. The `check_bathroom_spaciousness` tool reports on maneuverability right as your agent processes the data, which is perfect for frontends that need rapid feedback. Handling ramp requirements doesn't have to wait either. Using `check_ramp_compliance`, you get slope and landing details streamed back instantly. This capability makes complex checks feel fast and responsive.

Validating Physical Paths with Vercel AI SDK

The MCP handles physical dimensions like passages and corridors. Calling `check_corridor_and_passage` returns compliance status and violation details for any given path segment. This data is structured to be easily consumed by client-side components. It also checks the critical ramp requirements using `check_ramp_compliance`, verifying slope limits and necessary transition landings in one call. The Vercel AI SDK ensures this entire process feels snappy to the end user.

Setup guide

Set up Accessibility Checker 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 Checker 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 Checker 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 Checker. 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.

Why Choose Vinkius

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Common questions about Accessibility Checker MCP in Vercel AI SDK

It streams results directly into your front-end UI. You don't wait for a single large JSON response; you see compliance data appear in real time as it's being processed by your agent.

Yes, the MCP is built to verify against both USA and EU universal accessibility guidelines. It checks critical areas like restrooms and passages using structured tools.

The service touches building blueprints/dimensional measurements. Credentials pass through a zero-trust proxy, meaning your keys are used only in transit and never stored on disk.

It processes dimensional requirements like clear widths for doorways and corridors. It also handles structural details like ramp slopes and bathroom maneuverability spaces.

Absolutely. You can chain calls, running checks on passages (`check_corridor_and_passage`) followed by doorway inspections (`check_doorway`), all within your streaming agent workflow.

Use it with your favorite AI tools

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