How to Use the Amazon Selling Partner MCP in Vercel AI SDK

Q: How do I connect the Amazon Selling Partner MCP Server to the Vercel AI SDK?

Run npm install ai @ai-sdk/mcp. Initialize it with createMCPClient({ transport: { type: "http", url: "YOURVINKIUSURL" } }). Call mcpClient.tools() and pass the array straight into your streamText function.

Q: Can the Vercel AI SDK handle Amazon Selling Partner report generation?

Yes. Your agent initiates the process using createreport. Since reports take time to compile, the agent can periodically check getreportstatus while streaming progress updates to the user's UI.

Q: How do I clean up the connection after fetching order items?

Always call mcpClient.close() when your route handler finishes. This frees up the connection after your agent finishes checking getorderitems and streaming the response.

Stream live Amazon marketplace data directly into your React frontends using the Vercel AI SDK. No loading spinners, just real-time syncs.

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Connect Amazon Selling Partner MCP to Vercel AI SDK

Create your Vinkius account to connect Amazon Selling Partner 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 Amazon Selling Partner with Vercel AI SDK

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Stream FBA Inventory to the UI

Streaming FBA inventory directly to your merchants prevents them from waiting three seconds for a dashboard to render. Connect this MCP Server to your Next.js app and watch stock levels appear instantly. The `list_fba_inventory` tool pipes live warehouse counts straight through the Vercel AI SDK into your frontend components. Users see the exact moment an item drops below safety thresholds. You trigger `get_catalog_item` to pull the ASIN details, and the agent streams the title and current status directly into the DOM before the database even thinks about caching it.

Vercel AI SDK Financial Sync

Stop building custom polling hooks to track seller fees and refunds. When a user asks about their recent payouts, the agent fires off `list_financial_events` and streams the transaction breakdown row by row into your Svelte table component. If the query requires a deeper dive, the agent chains a `create_report` call to generate the GET_MERCHANT_LISTINGS_ALL_DATA payload. It checks progress with `get_report_status`, keeping the user updated via streamed text chunks while the heavy lifting happens in the background.

Real-Time Order Management

Customer service dashboards usually require massive backend infrastructure to pull Amazon order data. Bypass that entirely. Your React app can call `list_orders` directly from the edge, pulling pending shipments without touching your main database. When an agent needs to inspect a specific purchase, it grabs the exact line items using `get_order_items`. The Vercel AI SDK handles the HTTP transport and tool execution, streaming the buyer's shipping tier and item condition straight into your support rep's view.

Setup guide

Set up Amazon Selling Partner 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 Amazon Selling Partner 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 Amazon Selling Partner 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 Amazon Selling Partner. 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 Amazon Selling Partner MCP in Vercel AI SDK

Run `npm install ai @ai-sdk/mcp`. Initialize it with `createMCPClient({ transport: { type: "http", url: "YOUR_VINKIUS_URL" } })`. Call `mcpClient.tools()` and pass the array straight into your `streamText` function.

Yes. Your agent initiates the process using `create_report`. Since reports take time to compile, the agent can periodically check `get_report_status` while streaming progress updates to the user's UI.

It runs perfectly at the edge. The MCP client uses standard HTTP transport, meaning you can pull `list_marketplaces` or search catalogs from edge runtimes without Node.js dependencies.

Always call `mcpClient.close()` when your route handler finishes. This frees up the connection after your agent finishes checking `get_order_items` and streaming the response.

Vinkius executes every request inside an ephemeral V8 Isolate Sandbox. When your agent pulls ASINs, stock counts, or financial events, the memory space is destroyed immediately after the response ships. Nothing persists.

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