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How to Use the Azure Service Bus Topic MCP in Vercel AI SDK

Give your Vercel AI SDK frontends the ability to trigger cloud events by firing messages straight into an Azure Service Bus Topic.

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Vercel AI SDK

Connect Azure Service Bus Topic MCP to Vercel AI SDK

Create your Vinkius account to connect Azure Service Bus Topic 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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Send Cloud Events from Vercel AI SDK

The `publish_message` tool wires your React frontend straight into your messaging backbone. When a user types a command in your app, the AI SDK streams the thought process to the screen while simultaneously pushing the payload to Azure. You inject the Vinkius endpoint token via your `authProvider` and set up the HTTP transport. The agent formats the message and dispatches it, letting your Next.js app trigger backend workers without waiting for a separate API call to resolve.

Route Messages with Custom Properties

Downstream subscriptions rely on metadata to filter incoming traffic. The `publish_message` tool accepts a `customProperties` JSON object right alongside the main text payload. Because this MCP Server accepts dynamic inputs, your AI agent decides on the fly who handles the event. It sets the exact headers required, ensuring your background workers pick up the right jobs instantly.

Fire and Forget from the Edge

Firing payloads at an MCP Server works flawlessly inside Edge Functions. You initialize the client, fetch the remote tools, and pass them directly into your `streamText` function. The agent finishes thinking, calls the tool, and you immediately run `mcpClient.close()`. The user sees the confirmation render in real-time, while Azure handles the asynchronous heavy lifting behind the scenes.

Setup guide

Set up Azure Service Bus Topic 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. 1

    Install dependencies

    Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).

  2. 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. 3

    Discover and use tools

    Call mcpClient.tools() to auto-discover all Azure Service Bus Topic tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.

  4. 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 Azure Service Bus Topic transactions",
});

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

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Azure Service Bus Topic. 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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Built-in savings

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Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Azure Service Bus Topic MCP in Vercel AI SDK

Pass your Vinkius URL into `createMCPClient` using the HTTP transport option. Then call `mcpClient.tools()` and inject the results into your `streamText` function.
Yes. The tool accepts a `customProperties` parameter. Your agent populates this JSON object to control which downstream subscriptions receive the payload.
No. You should always call `mcpClient.close()` as soon as the `streamText` operation finishes. This frees up resources and prevents hanging connections.
The AI SDK streams the tool call state to the frontend. You can render a loading indicator or a success badge in your React component the moment the tool fires.
Vinkius runs the MCP Server in an ephemeral V8 isolate that shuts down immediately after execution. The text and custom JSON metadata you send to your topic exist only in memory during the split-second transmission and are never logged or stored.

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