How to Use the NCREIF MCP in Vercel AI SDK

Q: How do I add NCREIF tools to my Vercel AI SDK project?

Install @ai-sdk/mcp and create an MCP client pointing to the Vinkius endpoint to let your Vercel AI SDK agent query commercial real estate indices. You then pass the tools from mcpClient.tools() directly into generateText or streamText to fetch NCREIF returns.

Stream institutional NCREIF property returns and fund metrics directly into your React components using the Vercel AI SDK.

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Connect NCREIF MCP to Vercel AI SDK

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

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Stream property returns to Vercel AI SDK frontends

The `get_property_returns` tool pulls institutional real estate returns directly into your Next.js edge functions using this MCP Server. Your Vercel AI SDK client calls this tool to retrieve historical asset returns and immediately renders the output on-screen without making the user wait for a full page reload. By combining this tool with `list_properties`, you can build dynamic React dashboards that update as your agent fetches commercial asset data. Don't worry about slow database queries; this setup lets Vercel AI SDK users inspect NCREIF real estate trends in real time.

Track ODCE fund performance with this MCP Server

The `get_fund_performance` tool retrieves performance metrics for major open-end diversified core equity funds. Your AI client uses this tool to compare NCREIF fund yields and net asset values directly within your Vercel AI SDK interface. You can pair this with `list_funds` to let users filter real estate funds by vintage or strategy. The streaming UI updates instantly, showing institutional investors how different funds stack up against their benchmarks.

Map regional real estate trends instantly

The `get_region_data` tool fetches commercial property performance metrics broken down by geographic territories. Your AI client invokes this tool to isolate regional growth patterns and feed them directly into your Vercel AI SDK chart components. Using `get_property_type_data` alongside regional metrics helps you spot diverging trends between industrial and office sectors. Developers build live Next.js dashboards where users can toggle regions and see asset-class performance update on the fly.

Setup guide

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

Install `@ai-sdk/mcp` and create an MCP client pointing to the Vinkius endpoint to let your Vercel AI SDK agent query commercial real estate indices. You then pass the tools from `mcpClient.tools()` directly into `generateText` or `streamText` to fetch NCREIF returns.

Yes, this MCP server is compatible with Vercel AI SDK edge runtimes, allowing `get_index_data` to stream institutional real estate performance metrics directly to Next.js components. This bypasses cold-start delays when loading NCREIF indices.

The SDK automatically parses the JSON schema generated by tools like `list_indices` or `list_market_data` to construct precise queries. Your Vercel AI SDK agent reads these parameters to fetch specific real estate markets.

No, the SDK handles the tool-call lifecycle automatically. When the agent uses `get_property_type_data`, the NCREIF returns are injected directly into the chat state, updating your React components automatically.

Your queries for NCREIF fund returns and property performance metrics are executed in an isolated V8 sandbox on our MCP Server. No NCREIF API keys or proprietary investment queries are exposed to the public internet or stored on external servers.

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