How to Use the Greenhouse MCP in Vercel AI SDK

Q: Can the Vercel AI SDK update Greenhouse records?

Yes. You can use tools like updatecandidate or rejectapplication directly in your chat flows. The AI executes the change, and you get the confirmation back in your stream.

Stream Greenhouse candidate data directly into your Vercel AI SDK interface for real-time hiring updates.

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Connect Greenhouse MCP to Vercel AI SDK

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

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Live Greenhouse tracking with AI SDK

Feed your UI live candidate data by hooking `list_candidates` and `get_candidate_details` into your streamText calls. You get actual recruitment status updates appearing for your users as the AI pulls them. Stop waiting for state updates. Your frontend renders the Greenhouse metadata the moment the tool finishes, keeping your hiring dashboard current without extra polling.

Automated pipeline management

Push candidates through your hiring stages using `advance_application` directly from your React components. Triggering these actions via the AI SDK keeps your workflow moving without manual tab-switching. When a candidate hits a milestone, your application logic handles the Greenhouse transition immediately. It's just a tool call that executes on the server and updates your view.

Instant Greenhouse job lookup

Query your active hiring needs using `list_open_jobs` and `get_job_details` within your edge functions. The AI SDK fetches these requirements and displays them to the user instantly. Keep your job board synced with your internal recruitment platform. You'll see the exact metadata returned by the server, ensuring your application always shows the current role requirements.

Setup guide

Set up Greenhouse 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 Greenhouse 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 Greenhouse 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 Greenhouse. 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 Greenhouse MCP in Vercel AI SDK

Use the @ai-sdk/mcp package to initialize the client. You'll point it at your Vinkius endpoint and pass the tools into your agent definition.

Yes. You can use tools like `update_candidate` or `reject_application` directly in your chat flows. The AI executes the change, and you get the confirmation back in your stream.

It does. Because the AI SDK supports streaming tool results, the data appears as soon as the MCP server finishes the request.

Vinkius handles the connection securely. You only need to provide the endpoint token, keeping your sensitive API keys out of your codebase.

Your candidate names and contact info remain within your infrastructure. The MCP server acts as a secure bridge, and your data never touches third-party storage.

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