How to Use the Dyte MCP in Mastra AI

Q: Does Mastra AI support human approval for Dyte actions?

You can enable requireToolApproval in your agent config. This forces the agent to pause before calling tools like createmeeting until you give the green light.

Q: How do I list all Dyte meetings in a Mastra AI workflow?

You call listmeetings as part of your agent's tool set. The agent returns an array of active sessions, which you can then filter or process in your workflow branches.

Deploy complex video workflows in Mastra AI. Automate meeting orchestration with built-in retry logic and error handling.

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Setup Dyte with Mastra AI

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Orchestrate Dyte meetings in Mastra AI

Build agent workflows that handle meeting creation as a multi-step process. Your agent uses `create_meeting` to set up sessions, then stores the ID in memory for subsequent actions. If the initial call fails, the Mastra framework manages the retry logic. This ensures your sessions are created even when network conditions fluctuate.

Conditional media management

Trigger recordings based on meeting events. Your agent evaluates the session context and calls `start_recording` or `stop_recording` as part of a larger, automated workflow. This logic keeps your storage costs predictable. The agent only initiates media processing when specific criteria are met within the Mastra workflow engine.

Participant lifecycle automation

Automate the onboarding of users into your video sessions. Your Mastra agent checks meeting status with `get_meeting` and adds users with `add_participant` at the right moment. This prevents orphaned meetings. The agent tracks the lifecycle from initiation to termination, ensuring every resource is accounted for.

Setup guide

Set up Dyte MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Dyte tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "dyte-mcp-client",
  servers: {
    "dyte-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Dyte Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Dyte tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Dyte transactions"
);
console.log(result.text);

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Common questions about Dyte MCP in Mastra AI

You initialize the server by passing the Vinkius URL to the `MCPClient` constructor. Once added, you spread the available tools into your agent definition.

You can enable `requireToolApproval` in your agent config. This forces the agent to pause before calling tools like `create_meeting` until you give the green light.

Mastra handles retries with exponential backoff for every tool call. If the Dyte API is temporarily busy, the agent attempts the operation again automatically.

Vinkius manages all transport security. Only the session IDs, participant tokens, and recording status strings are processed by the server, ensuring your private meeting data stays isolated.

You call `list_meetings` as part of your agent's tool set. The agent returns an array of active sessions, which you can then filter or process in your workflow branches.

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