How to Use the Beisen (iTalentX) MCP in Vercel AI SDK

Q: How do I connect Beisen (iTalentX) to the Vercel AI SDK?

You'll use the createMCPClient function from @ai-sdk/mcp. Just pass your unique Vinkius endpoint URL for the Beisen (iTalentX) server in the transport options. Then you can provide the tools to generateText or streamText.

Q: Can I filter employees with the Vercel AI SDK and Beisen (iTalentX)?

Yes. Your AI client can first call listemployees to get a full list from Beisen (iTalentX). Then, you can instruct your agent to filter that list based on department, position, or other criteria before displaying it in your Vercel AI SDK-powered application.

Q: What's the best way to display Beisen (iTalentX) interview lists in a Next.js app with the Vercel AI SDK?

The best approach is to stream the results. Use the streamText function and have your AI client call the listinterviews tool. As the tool returns each interview, you can render it into a list component, giving the user immediate feedback.

Build live HR dashboards with the Vercel AI SDK. Stream Beisen (iTalentX) data directly into your React or Next.js components.

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Connect Beisen (iTalentX) MCP to Vercel AI SDK

Create your Vinkius account to connect Beisen (iTalentX) 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 Beisen (iTalentX) with Vercel AI SDK

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Live Employee Profiles

Stop making users wait. Use the Vercel AI SDK to build an internal HR tool where employee data appears as it's fetched. Your AI client can call `get_employee` and `get_attendance_records`, and the results stream directly into your UI components. This makes your frontends feel incredibly fast. The end user sees names, departments, and attendance details populating in real-time, not after a loading spinner finishes. It’s a much better way to interact with the data stored in your Beisen (iTalentX) system.

Real-Time Recruiting Pipelines

Build a recruiting dashboard that's always up to date. Your agent can use `list_recruitment_applications` and `list_interviews` from the Beisen (iTalentX) server to populate a live-updating kanban board or list. Because the AI SDK handles the streaming connection to the MCP Server, you just focus on writing your UI. New applications and scheduled interviews from Beisen (iTalentX) flow right in, giving hiring managers an immediate, accurate view of their pipeline.

Interactive Org Charts

Give executives a dashboard that actually answers questions. Your agent can start by showing top-level metrics from `get_org_summary` and `get_payroll_summary`. The data streams directly into your charts and graphs. This isn't just a static report. When a user asks a follow-up question, your agent can dig deeper with tools like `list_departments` or `list_employees`, streaming the new data without a full page reload. It's a genuinely interactive way to explore your organization's data.

Setup guide

Set up Beisen (iTalentX) 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 Beisen (iTalentX) 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 Beisen (iTalentX) 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 Beisen (iTalentX). 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 Beisen (iTalentX) MCP in Vercel AI SDK

You'll use the `createMCPClient` function from `@ai-sdk/mcp`. Just pass your unique Vinkius endpoint URL for the Beisen (iTalentX) server in the transport options. Then you can provide the tools to `generateText` or `streamText`.

Yes. Your AI client can first call `list_employees` to get a full list from Beisen (iTalentX). Then, you can instruct your agent to filter that list based on department, position, or other criteria before displaying it in your Vercel AI SDK-powered application.

The best approach is to stream the results. Use the `streamText` function and have your AI client call the `list_interviews` tool. As the tool returns each interview, you can render it into a list component, giving the user immediate feedback.

Yes, this specific MCP Server provides read-only access to your Beisen (iTalentX) instance. All available tools, like `get_employee` and `list_positions`, are designed to fetch information, not create or modify it.

Your employee records and attendance data are secure. Vinkius processes every request from your AI client in an ephemeral, zero-trust environment. Your single authentication token handles access, and no data persists on the MCP Server after the request is complete.

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