How to Use the Checkr MCP in Vercel AI SDK

Q: How do I start a Checkr background check using the Vercel AI SDK?

First, create a candidate with createnewcandidate. Then, pass the resulting candidate ID to the startbackgroundcheck tool. The AI SDK will stream the results of the tool call directly into your application.

Q: Can I show live Checkr report updates in my Next.js app with the AI SDK?

Yes. Have your agent call listbackgroundreports periodically. The AI SDK's streaming capabilities will push any changes to your Next.js components, so your UI updates without a full page reload.

Build UIs that stream Checkr background check statuses live with the Vercel AI SDK.

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Connect Checkr MCP to Vercel AI SDK

Create your Vinkius account to connect Checkr 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 Checkr with Vercel AI SDK

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Live Candidate Onboarding

Your agent calls `create_new_candidate`, and the new profile instantly appears in your UI. No spinners. Next, it triggers `start_background_check` with the right package, and your user sees the status change to "in progress" in real time. This works because the AI SDK streams the tool's JSON output directly into your React components. You just map the data to your UI. This MCP Server handles the Checkr API calls, so you can focus on building a fast front-end experience.

Real-Time Report Monitoring

Stop making users refresh the page. Your agent can poll `list_background_reports`, and the AI SDK will stream any changes directly to your dashboard. New reports appear at the top. Status changes from 'pending' to 'clear' happen live. When a user clicks for more information, your agent calls `get_report_details`. The specifics of the report—adjudication status, turnaround time—stream directly into a modal or detail view. It feels fast because it is.

Dynamic Screening with the AI SDK

Let your agent offer choices. Use `list_screening_packages` to pull your available Checkr packages. The AI SDK can render these options in the UI, letting a user or another process choose the right background check for a specific role. This Checkr MCP server turns complex API calls into simple functions your agent can run. The Vercel AI SDK makes it trivial to display the results. You get a secure, production-ready integration without writing boilerplate API client code.

Setup guide

Set up Checkr 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 Checkr 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 Checkr transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Checkr. 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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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Common questions about Checkr MCP in Vercel AI SDK

First, create a candidate with `create_new_candidate`. Then, pass the resulting candidate ID to the `start_background_check` tool. The AI SDK will stream the results of the tool call directly into your application.

Yes. Have your agent call `list_background_reports` periodically. The AI SDK's streaming capabilities will push any changes to your Next.js components, so your UI updates without a full page reload.

Vinkius handles it for you. You get a single endpoint token to put in your `createMCPClient` configuration. You don't have to manage OAuth or expose your private Checkr keys on the client-side.

You can manage the entire background check lifecycle. The tools let you create candidates, list available screening packages, start checks, and get detailed status reports. You can see everything from invitation status to the final report adjudication.

The Checkr MCP Server runs in an ephemeral sandbox for each request. Candidate PII is only held in memory for the moment it's needed to communicate with Checkr's API. Vinkius handles the auth token, so your keys are never exposed in your frontend code.

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