How to Use the Agify MCP in Vercel AI SDK

Get real-time age estimates in your Vercel AI SDK app with Agify.

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Connect Agify MCP to Vercel AI SDK

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

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Stream age predictions directly to your Vercel AI SDK UI

Pipe the `predict_age` tool directly into your streaming response. Your frontend renders the data the moment it arrives without waiting for a full turn. This MCP Server maintains an open connection to the Agify API, ensuring your users see the results as they arrive in the browser.

Handle batch name processing within Vercel AI SDK routes

Feed an array of names into `predict_age_batch` to process multiple identity profiles at once. The output maps directly to your state management logic. Your edge functions handle the computation cleanly. You avoid the lag of sequential API calls by grouping your requests into a single execution.

Deploy Agify data to the edge

Run your MCP Server logic inside Vercel edge functions for low-latency response times. The protocol overhead stays minimal, keeping your bundle size lean. Everything happens on the request path. You get the name-to-age mapping finished before the user finishes reading their notification.

Setup guide

Set up Agify 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 Agify 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 Agify transactions",
});

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

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Common questions about Agify MCP in Vercel AI SDK

Install the necessary packages and initialize the client with your Vinkius endpoint. Pass the tools into your generateText call to start querying names immediately.

Yes, the tools are designed for streamText. You push the tool result into the stream and the UI updates instantly.

You can narrow your predictions by passing a country code to the tool. This helps if you have a specific regional audience in mind.

We only send the first name strings to the API. Your endpoint token keeps the traffic isolated from other users.

The server processes first name strings and country codes. No personal identifiers or historical logs are stored on our end.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.