How to Use the NVIDIA Audio MCP in Vercel AI SDK

Stream audio transcription and voice synthesis directly into your Vercel AI SDK frontends for real-time user experiences.

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Connect NVIDIA Audio MCP to Vercel AI SDK

Create your Vinkius account to connect NVIDIA Audio 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 NVIDIA Audio with Vercel AI SDK

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Real-time speech transcription in Vercel AI SDK

Pipe raw audio URLs directly into `speech_to_text` and watch the transcript stream into your React components. This eliminates the delay users expect from traditional file processing. Your UI updates as the text arrives. Using `punctuate_text` ensures the output looks clean before it hits the DOM.

Dynamic voice generation for Vercel AI SDK apps

Generate natural-sounding audio from your app's responses by calling `text_to_speech`. The MCP Server handles the conversion while your frontend keeps the stream alive. Want a specific tone? Pass a unique ID into the voice parameter. It ships as a standard blob your audio player can parse immediately.

Noise reduction for Vercel AI SDK input streams

Clean up noisy audio files before you process them with `cancel_noise`. Your users can upload rough recordings and get studio-quality results back. It runs at the edge. The cleaned file is ready for `classify_audio` or translation tasks within milliseconds.

Setup guide

Set up NVIDIA Audio 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 NVIDIA Audio 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 NVIDIA Audio transactions",
});

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

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Common questions about NVIDIA Audio MCP in Vercel AI SDK

Install the MCP client package and initialize the connection with your server URL. You then pass the tool list directly into your generateText function.

Yes. The tools return data that maps perfectly to the SDK's streaming hooks. You get a live flow of text or audio data without manual polling.

It is. The communication uses standard HTTP transports that work fine inside serverless environments. Keep your latency low by choosing the right region.

Pass your endpoint token through the authProvider configuration in your client setup. The server validates this before executing any tool requests.

No. The server processes the URL provided and clears the memory buffer immediately after the task finishes. We do not persist your input audio.

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