How to Use the ARGUS Cloud MCP in Vercel AI SDK

Q: How do I connect Vercel AI SDK to ARGUS Cloud?

Install @ai-sdk/mcp and initialize the MCP Server connection via createMCPClient with your Vinkius endpoint URL. Pass the result of mcpClient.tools() directly into your generateText or streamText calls.

Q: How do I check my ARGUS Cloud connection in Vercel AI SDK?

Call the getaccountcheck tool before executing heavy queries. This verifies your token is valid before you attempt to pull down massive commercial real estate portfolios.

Q: What is the best way to handle large portfolios?

Query the high-level structures using listportfolios first. Then let the user select a specific group, triggering getportfolio to stream the deeper financial metrics into the UI.

Stream commercial real estate valuations directly into your React frontends using the ARGUS Cloud MCP Server for Vercel AI SDK.

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Connect ARGUS Cloud MCP to Vercel AI SDK

Create your Vinkius account to connect ARGUS Cloud 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 ARGUS Cloud with Vercel AI SDK

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Stream ARGUS Cloud assets to React

The `list_assets` tool pulls your entire commercial real estate inventory straight from ARGUS. You pass the resulting JSON to Vercel AI SDK's `streamText` function to render property details live in the browser. Users watch building metrics appear instantly instead of staring at a loading state. Drilling down works the same way. When a user clicks a specific property, your app calls `get_asset` to fetch valuation models and current occupancy rates. The AI client formats this raw financial data into human-readable components on the fly.

Connect this MCP Server to Next.js

Integrating the `list_portfolios` tool requires just a few lines of TypeScript. You configure `createMCPClient` with your Vinkius HTTP endpoint and spread the tools into your Next.js API route. The edge function handles the request and pipes the portfolio structure back to the client. Fetching deep portfolio metrics uses the `get_portfolio` endpoint. Because Vercel AI SDK supports edge environments natively, these heavy financial aggregations resolve quickly. You must remember to call `mcpClient.close()` after fetching the data to prevent hanging connections.

Render real-time property alerts

Property managers need to know about lease expirations and valuation shifts immediately. The `list_notifications` tool grabs recent alerts from your ARGUS account and pushes them to your frontend. You bind these events to toast notifications or dashboard widgets. Before querying these alerts, you validate the connection state using `get_account_check`. Vercel AI SDK handles the OAuth flow through its `authProvider` configuration, keeping the session active while users browse their real estate data.

Setup guide

Set up ARGUS Cloud 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 ARGUS Cloud 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 ARGUS Cloud 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 ARGUS Cloud. 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 ARGUS Cloud MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and initialize the MCP Server connection via `createMCPClient` with your Vinkius endpoint URL. Pass the result of `mcpClient.tools()` directly into your `generateText` or `streamText` calls.

Yes. The Vercel AI SDK integration runs perfectly on the edge. You fetch property data via `list_assets` and stream the response to the client without hitting cold start limits.

Call the `get_account_check` tool before executing heavy queries. This verifies your token is valid before you attempt to pull down massive commercial real estate portfolios.

Query the high-level structures using `list_portfolios` first. Then let the user select a specific group, triggering `get_portfolio` to stream the deeper financial metrics into the UI.

Vinkius runs this MCP Server inside a V8 Isolate Sandbox. Your property valuations, lease terms, and occupancy rates fetched via `get_asset` never persist on our infrastructure. The sandbox spins down the moment your edge function closes the connection.

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