How to Use the AssemblyAI MCP in Vercel AI SDK

Q: How do I list previous AssemblyAI transcripts in Vercel AI SDK?

Call the listtranscripts tool through your agent. The SDK streams the returned array straight into your UI components.

Stream AssemblyAI transcription data straight into your Next.js frontends using the Vercel AI SDK.

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Connect AssemblyAI MCP to Vercel AI SDK

Create your Vinkius account to connect AssemblyAI 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 AssemblyAI with Vercel AI SDK

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Stream transcripts via Vercel AI SDK MCP Server

Call `transcribe_audio_url` from your server actions and watch the text appear live. Your agent grabs the audio source and pushes the parsed text directly to the React component tree. Users hate waiting for long podcast files to process. Using `get_transcript`, you pipe the current processing status right to the UI. The moment the file finishes, the text renders without a loading spinner.

Render speaker labels in real-time

Trigger `get_speakers` to map distinct voices to text blocks. Next.js catches the tool output and instantly formats the conversation like a chat interface. You do not need to wait for the entire file to finish before showing who said what. The SDK streams the speaker dictionary as it builds.

Extract and display sentiment data

Run `get_sentiments` to pull emotional context from the audio file. Your Svelte or Vue frontend updates a live dashboard showing positive or negative reactions across the timeline. Pulling `get_topics` works the exact same way. The agent categorizes the conversation and updates the UI state immediately, letting end users click through generated tags.

Setup guide

Set up AssemblyAI 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 AssemblyAI 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 AssemblyAI transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AssemblyAI. 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 AssemblyAI MCP in Vercel AI SDK

Install @ai-sdk/mcp and call createMCPClient. Pass the resulting tools into your streamText function so the agent can trigger audio processing.

Yes. You trigger the job with the audio URL and poll the status. The frontend stays responsive while the backend waits for the final text block.

Call the list_transcripts tool through your agent. The SDK streams the returned array straight into your UI components.

Always call mcpClient.close() when your edge function finishes. Leaving the connection open wastes resources and causes memory leaks in production.

The tools only pass audio URLs and text outputs through the Vinkius V8 isolate sandbox. Ephemeral environments destroy the session data immediately after the transcription finishes.

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