How to Use the AudD Music Recognition MCP in Vercel AI SDK

Grab song metadata and lyrics directly in your Vercel AI SDK interface with this MCP Server.

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Connect AudD Music Recognition MCP to Vercel AI SDK

Create your Vinkius account to connect AudD Music Recognition 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 AudD Music Recognition with Vercel AI SDK

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Real-time song identification for Vercel AI SDK

Trigger `recognize_music` to pull artist names and streaming links straight into your React components. Your users see the metadata populate as the AI processes the audio URL. This MCP Server handles the handshake, so you just pipe the output into your UI state. No extra heavy lifting on your backend.

Build lyric search into Vercel AI SDK apps

Use `search_lyrics` to let your users find tracks based on a few remembered lines. It returns the exact match and song metadata immediately. Your frontend receives the data as a clean JSON object. It’s perfect for building discovery features that feel snappy and responsive.

Track audio streams with Vercel AI SDK

Connect `add_monitored_stream` to keep an eye on incoming audio feeds without manual polling. It sets up a listener that watches for specific content. Once the hook fires, your `set_stream_callback_url` endpoint captures the result. It keeps your Vercel edge functions lean and focused on the user experience.

Setup guide

Set up AudD Music Recognition 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 AudD Music Recognition 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 AudD Music Recognition transactions",
});

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

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Common questions about AudD Music Recognition MCP in Vercel AI SDK

It acts as a bridge between your audio input and our recognition engine. You call the tools via the MCP client, and the results stream back into your app.

Yes. Since this MCP Server uses HTTP transport, your edge functions can reach out to it without blocking the event loop.

We keep your audio URLs and request data ephemeral. Vinkius handles the connection layer, so no sensitive logs persist after the request cycle finishes.

The tool returns a null result. Your logic should handle this empty state just like any other API failure.

No. The server only processes the URL you provide to identify the track. Your raw audio never hits our permanent storage.

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