How to Use the Gingr MCP in Vercel AI SDK

Q: How do I sync Gingr check-ins with Vercel AI SDK?

You hook the listactivecheckins tool into your streamText call. The Vercel AI SDK then handles the tool output as a streamable object, populating your UI instantly.

Q: Can I filter Gingr reservation data using Vercel AI SDK?

You can. By passing parameters from your client to listownerreservations, you pull only the specific booking history your agent needs to see.

Stream Gingr kennel data directly into your Vercel AI SDK interface for real-time pet care management.

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Connect Gingr MCP to Vercel AI SDK

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

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Live check-in monitoring with Vercel AI SDK

Feed live boarding data into your front-end components. Use `list_active_checkins` to show your staff exactly who is in the building, updating your UI components as the API responds. Your users won't see a loading spinner. The data streams from your MCP server directly into the view, keeping your kennel dashboard reactive and accurate.

Instant owner lookups in your React app

Connect your search bar to `find_owner_by_email` or `find_owner_by_phone`. This lets your agents pull up contact information the moment a client walks through the door. It removes the need for manual record digging. The system pushes the relevant profile details to the screen, allowing your staff to focus on the pet, not the database.

Verify Gingr connectivity in your edge functions

Run `verify_api_connection` as part of your server-side initialization. This ensures your app is talking to the correct facility endpoint before any data requests start. It catches authentication issues early. Your edge functions remain lean, only processing requests when the server confirms the connection is live.

Setup guide

Set up Gingr 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 Gingr 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 Gingr transactions",
});

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

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Common questions about Gingr MCP in Vercel AI SDK

You hook the `list_active_checkins` tool into your streamText call. The Vercel AI SDK then handles the tool output as a streamable object, populating your UI instantly.

Yes. The transport layer is designed for low-latency HTTP, making it a natural fit for edge environments where speed is the priority.

You can. By passing parameters from your client to `list_owner_reservations`, you pull only the specific booking history your agent needs to see.

Keep them in your environment variables. The server reads these at runtime to authenticate your requests without exposing them to the client-side code.

The server acts as a proxy. It touches only the necessary PII—like names and contact info—and uses ephemeral connections that close immediately after the task finishes.

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