How to Use the Pando MCP in Vercel AI SDK

Q: What happens if Pando API goes down in Vercel AI SDK?

You should use checkapistatus to ping the server before sending requests. It prevents your UI from hanging when the service is unreachable.

Stream real-time logistics data from Pando directly into your Vercel AI SDK frontends for live shipment tracking.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Pando MCP to Vercel AI SDK

Create your Vinkius account to connect Pando to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Pando with Vercel AI SDK

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Live status monitoring for Vercel AI SDK

Stop waiting for spinners. Use `check_api_status` to verify your connection and feed live shipment updates into your UI components instantly. Your users see cargo status changes as they happen. It’s built for React and Next.js, keeping your interface synced with the Pando backend.

Instant indent management in your app

Trigger `create_indent` directly from your event handlers. You pass JSON data, and the system processes the request without manual input. It handles the heavy lifting of logistics creation. Your frontend remains responsive while the agent executes the request in the background.

Granular data access for custom dashboards

Use `list_shipments` and `get_shipment_details` to pull specific records into your view layer. You choose exactly what data lands on the screen. Developers gain full control over the information flow. You define how the Pando data appears to the end user without extra bloat.

Setup guide

Set up Pando 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 Pando 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 Pando transactions",
});

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

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