How to Use the Medusa (Headless E-commerce Engine) MCP in Vercel AI SDK

Q: How does the Medusa (Headless E-commerce Engine) MCP Server connect to my Vercel AI SDK application?

You initialize the connection using the @ai-sdk/mcp package. This setup exposes the 10 core commerce tools directly to your text generation models. You stream the raw output straight into your React or Next.js components.

Q: Can I use Vercel AI SDK to display products fetched via Medusa (Headless E-commerce Engine)?

Yes, by passing listproducts or listcollections directly to the tool parameters in streamText. The model processes the raw JSON and generates structured UI components immediately. This eliminates client-side loading states for your shoppers.

Q: Does this MCP Server support localized checkout flows in Vercel AI SDK?

It does. The agent calls getstoreconfig and listregions to identify tax rates and active payment providers. This ensures your Vercel AI SDK interface displays accurate checkout details before triggering payment steps.

Stream Medusa (Headless E-commerce Engine) catalog and order data directly into your Vercel AI SDK frontend in real-time.

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Connect Medusa (Headless E-commerce Engine) MCP to Vercel AI SDK

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Setup Medusa (Headless E-commerce Engine) with Vercel AI SDK

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Stream real-time product catalogs in Vercel AI SDK

`list_products` feeds raw catalog data directly into your streaming UI components. Your AI client pulls active inventory details, prices, and options using `get_product` without hitting slow intermediate backend layers. Users get instant feedback as the model generates options. You avoid the typical loading spinner lag because the JSON payload feeds the Vercel AI SDK component state directly at the edge.

Handle orders and payments through Vercel AI SDK

`get_order` retrieves complete transactional states including shipping addresses and line items instantly. If a customer wants to complete their purchase, the agent calls `capture_payment` to settle the balance. Edge functions execute these calls closer to your database. This architectural setup prevents cold-start delays from ruining the checkout experience.

Inspect customer profiles using this MCP Server

`get_customer` exposes specific user profiles to tailor the chat experience based on past store interactions. By querying `list_regions` and `get_store_config`, your Vercel AI SDK application automatically formats tax rates and currency symbols for the visitor's location. You don't have to build custom middleware to map regional commerce rules. The server delivers the exact schema your frontend needs to show localized pricing on the fly.

Setup guide

Set up Medusa (Headless E-commerce Engine) 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 Medusa (Headless E-commerce Engine) 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 Medusa (Headless E-commerce Engine) transactions",
});

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

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Common questions about Medusa (Headless E-commerce Engine) MCP in Vercel AI SDK

You initialize the connection using the `@ai-sdk/mcp` package. This setup exposes the 10 core commerce tools directly to your text generation models. You stream the raw output straight into your React or Next.js components.

Yes, by passing `list_products` or `list_collections` directly to the tool parameters in `streamText`. The model processes the raw JSON and generates structured UI components immediately. This eliminates client-side loading states for your shoppers.

It does. The agent calls `get_store_config` and `list_regions` to identify tax rates and active payment providers. This ensures your Vercel AI SDK interface displays accurate checkout details before triggering payment steps.

This MCP tool interacts directly with your configured Medusa payment providers. Your frontend never touches raw credit card data. The server passes the payment identifier securely to complete the transaction.

Vinkius runs this connector inside a secure, zero-trust V8 isolate sandbox. Every request to `get_customer` or `list_orders` utilizes ephemeral tokens that expire immediately after the tool execution. No sensitive customer records or transactional data are stored on our servers.

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