How to Use the Hunter MCP in Vercel AI SDK

Q: How do I stream Hunter email search results using Vercel AI SDK?

You call mcpClient.tools() to fetch the MCP tools and pass them directly to streamText. When the AI invokes searchdomainemails, the tool results stream straight to your React components in real-time.

Q: What happens if a domain search returns too many leads?

Your AI client can check getdomainemailcount first to gauge the volume. If the count is high, it can paginate the results using searchdomainemails to avoid hitting token limits.

Q: How does this server secure my lead lists and verified emails?

Every email verified through verifyemailaddress is processed inside an ephemeral, zero-trust V8 isolate. No lead data or contact lists are ever saved to persistent storage on the Vinkius platform.

Stream real-time email verification and lead discovery directly to your React app with Vercel AI SDK.

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Connect Hunter MCP to Vercel AI SDK

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

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Claude

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Instant UI updates with `ai-sdk` and Hunter

When your user types a domain, your React UI shouldn't hang on a loading spinner. Your AI client grabs lead volume instantly using `get_domain_email_count` and streams that count straight to the browser. This Vercel AI SDK setup executes the tool call on the edge. It renders the results as they arrive, keeping your interface fast and interactive.

Real-time lead verification on the Edge

Build a high-speed verification widget that handles list cleaning without server-side lag. By calling `verify_email_address` through this MCP Server, your streaming client checks deliverability and renders status indicators line-by-line. You configure the MCP client using `createMCPClient` to link the endpoint. The AI processes the verification queue, streaming raw deliverability metrics to the frontend before closing with `mcpClient.close()`.

Direct contact discovery in your Next.js chat

Let users find key contacts during active conversations by running `find_person_email` directly inside your chat window. The AI client searches for the target name and domain, then instantly streams the verified email back to the UI. You can immediately follow up by calling `create_new_lead` to save that contact without forcing the user to click a save button. This keeps your user experience fluid and entirely conversational.

Setup guide

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

You call `mcpClient.tools()` to fetch the MCP tools and pass them directly to `streamText`. When the AI invokes `search_domain_emails`, the tool results stream straight to your React components in real-time.

Yes, because this MCP Server runs on Vinkius sandboxes, your edge code remains lightweight. You just call `verify_email_address` through a standard HTTP transport without heavy dependencies.

Vinkius manages the MCP credentials on its secure proxy, meaning your frontend never sees them. You only pass a single Vinkius endpoint token to `createMCPClient` to start querying.

Your AI client can check `get_domain_email_count` first to gauge the volume. If the count is high, it can paginate the results using `search_domain_emails` to avoid hitting token limits.

Every email verified through `verify_email_address` is processed inside an ephemeral, zero-trust V8 isolate. No lead data or contact lists are ever saved to persistent storage on the Vinkius platform.

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