How to Use the Dyte MCP in Vercel AI SDK

Q: Will my Vercel AI SDK app handle Dyte participant lists?

It will. Your agent calls listparticipants to fetch live data from the meeting, which then feeds into your UI components for immediate display.

Build real-time video experiences in your Vercel AI SDK apps. Automate meeting lifecycles without leaving your front-end code.

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…and any MCP-compatible client

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Connect Dyte MCP to Vercel AI SDK

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

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Direct Dyte control in Vercel AI SDK

Your AI agent handles meeting logistics instantly. When a user requests a session, the agent triggers `create_meeting` and returns the join token directly to your UI. This removes the need for custom back-end routing. The tools stream results back to the interface, so your users see the meeting status update the moment the API responds.

Manage live streams and recordings

Control session media outputs programmatically. Your agent monitors the stream state and executes `start_recording` or `start_livestream` based on user-defined triggers in your chat interface. Stopping these events is just as simple. Once the session wraps, the agent calls `stop_recording` to finalize the media assets for later playback.

Real-time participant oversight

Keep your dashboard in sync with actual meeting attendance. The agent uses `list_participants` to pull current user data and display it within your Vercel AI SDK components. You get an accurate count of who is in the room without manual refresh cycles. It handles the heavy lifting of state management while your front-end remains responsive.

Setup guide

Set up Dyte 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 Dyte 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 Dyte transactions",
});

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

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Common questions about Dyte MCP in Vercel AI SDK

You connect by initializing the MCP client with your specific Vinkius endpoint. Pass the tools you get from `mcpClient.tools()` directly into your `generateText` or `streamText` calls.

Yes. Your agent creates the meeting via the MCP server, provides the participant with a unique join token, and manages the session lifecycle from start to finish.

It will. Your agent calls `list_participants` to fetch live data from the meeting, which then feeds into your UI components for immediate display.

The server uses Vinkius-managed authentication tokens to secure every request. It only transmits meeting metadata and user identifiers over encrypted channels.

You can configure storage settings directly when the agent calls `start_recording`. The tool manages the session media state while your application handles the resulting data.

Use it with your favorite AI tools

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