How to Use the Nestoria MCP in Vercel AI SDK

Q: How do I use Nestoria search results from the Vercel AI SDK in my Next.js app?

You'll use the streamText function and pass it the searchlistings tool. The SDK streams structured JSON for each property found, which you can then render inside a React Server Component or client component.

Q: Can I filter Nestoria search results by price and number of bedrooms using the Vercel AI SDK?

Yes. The searchlistings tool accepts parameters for pricemin, pricemax, and bedroommin. Your agent can pass these arguments when it calls the tool, giving you fine-grained control over the search.

Stream Nestoria property data directly into your UI with the Vercel AI SDK. No loading spinners, just real-time results.

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Connect Nestoria MCP to Vercel AI SDK

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

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Find Properties, Live in Your UI

The `search_listings` tool connects your agent to Nestoria's global real estate database. You can search for properties to buy or rent, filtering by country, price, and more. With the Vercel AI SDK, you don't just fetch a list. You stream the search results directly into your React or Next.js components. Users see properties appearing on the screen one by one, which makes your application feel incredibly fast and responsive.

Build Frontends on a Live MCP Server

Connecting your app is simple. Use `createMCPClient` to point to the Vinkius endpoint, get the tools, and pass them to `generateText`. The SDK handles the streaming connection for you. This setup is perfect for building interactive search interfaces. Your agent uses the `search_listings` tool on the backend, and the structured JSON results stream directly to the frontend. You can map that live data straight to your UI elements without any extra parsing.

Filter Globally, Render Locally

Give your users a powerful property finder. Let them search for apartments in Tokyo or houses in Texas from the same interface. Your agent queries Nestoria with the exact filters needed. Because the Vercel AI SDK works in edge functions, your app stays fast no matter where your users are. It's a direct, live connection between your UI and a global property database, managed by this MCP server.

Setup guide

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

You'll use the `streamText` function and pass it the `search_listings` tool. The SDK streams structured JSON for each property found, which you can then render inside a React Server Component or client component.

Yes. The `search_listings` tool accepts parameters for `price_min`, `price_max`, and `bedroom_min`. Your agent can pass these arguments when it calls the tool, giving you fine-grained control over the search.

When the tool stream completes without yielding any objects, you know the search returned nothing. You can easily check for this in your code and render a 'No properties found' message in your UI.

No, Vinkius MCP servers don't cache application data. Every time your agent calls `search_listings`, it triggers a fresh query to the Nestoria API to get the most current listings available.

We don't store your query data. The Nestoria MCP server is ephemeral; it processes the search parameters like country or price, passes them to the Nestoria API, and streams the results back. Nothing about your specific property search is logged or saved.

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