How to Use the kvCORE MCP in Vercel AI SDK

Q: How do I connect kvCORE to the Vercel AI SDK?

Install the @ai-sdk/mcp package. You instantiate the connection using createMCPClient with an HTTP transport pointing to your Vinkius endpoint.

Q: Can the Vercel AI SDK stream kvCORE lead data to React?

Yes. Pass the tools to streamText and the UI updates as the MCP Server returns the data. You handle the rendering on the client side.

Q: Does this kvCORE MCP Server support OAuth via Vercel AI SDK?

It does. You pass your authProvider configuration directly into the client setup. That handles the token exchange before any API calls execute.

Stream real estate data straight into your Next.js frontend using the Vercel AI SDK.

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Connect kvCORE MCP to Vercel AI SDK

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

Ask AI about this MCP

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Claude

Perplexity

Live Lead Lookups

The `search_kvcore_leads` tool pulls lead IDs and basic contact info directly into your application. Your custom CRM dashboard needs this data fast. When an agent updates a phone number, `update_lead_info` pushes that JSON payload back to the database. Users don't want to stare at loading spinners. Because you built with this SDK, those lead records stream straight into the UI components as the AI fetches them. You get immediate visual feedback on every property search.

Map Property Listings via MCP Server

The `list_property_listings` tool exposes active inventory to your buyers. It returns the raw property arrays your map components require to plot markers. If a user clicks a specific pin, `get_listing_details` fetches the metadata for that exact address. You control exactly how this data renders. The MCP Server handles the backend query execution while your frontend manages the state. That keeps the architecture clean and the response times low.

Audit Agent Tasks

The `list_agent_tasks` tool grabs pending to-dos for any specific agent ID. Build an internal portal that tracks what your agents are actually doing. You can pair this with `get_agent_profile` to render a complete dashboard of who is working on what. Managers need visibility into the daily grind. Pulling `list_lead_activity` shows exactly when a lead was last contacted. Your custom interface turns that raw activity log into actionable charts.

Setup guide

Set up kvCORE 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 kvCORE 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 kvCORE 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 kvCORE. 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.

Why Choose Vinkius

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Common questions about kvCORE MCP in Vercel AI SDK

Install the `@ai-sdk/mcp` package. You instantiate the connection using `createMCPClient` with an HTTP transport pointing to your Vinkius endpoint.

Yes. Pass the tools to `streamText` and the UI updates as the MCP Server returns the data. You handle the rendering on the client side.

It does. You pass your `authProvider` configuration directly into the client setup. That handles the token exchange before any API calls execute.

The tool only reads the current database state. When they reconnect and sync, your next lookup will pull the updated record.

The server processes phone numbers and email addresses strictly in memory. The V8 Isolate Sandbox destroys the execution environment the millisecond the request finishes, leaving zero residual data.

Use it with your favorite AI tools

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