How to Use the Descript MCP in Mastra AI

Q: How do I handle Descript transcription failures in Mastra AI?

You define a workflow step using createtranscription and configure Mastra's automatic retry policy. If the Descript API hiccups, Mastra retries the step with exponential backoff before failing.

Q: Can a Mastra AI agent manage my Descript templates?

Yes. Your agent can call listtemplates to view available layouts, then use that data to structure new projects. This lets you automate consistent video formatting across your entire team.

Automate your Descript media pipelines with Mastra AI workflows using this MCP Server.

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Connect Descript MCP to Mastra AI

Create your Vinkius account to connect Descript to Mastra AI 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 Descript with Mastra AI

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Build resilient media pipelines with Mastra AI

The `create_transcription` tool handles heavy media uploads, making it the perfect starting point for a Mastra AI workflow. Once the transcription finishes, the workflow can use `get_transcription` to grab the text and pass it to the next step. If an error occurs, Mastra's built-in backoff system ensures your pipeline doesn't break.

Run complex conditional exports

The `create_export` tool lets your agent trigger video renders, while `list_exports` lets you monitor them until they finish. If the export succeeds, the workflow can automatically trigger a notification or post to your CMS. If it fails, Mastra branches the logic to notify your team, using the MCP tools to fetch error logs.

Automate project setups with templates

The `list_templates` tool lets your Mastra agent fetch pre-configured video layouts to automate new project setups. By combining `list_drives` and `list_projects`, your agent ensures the new project lands in the correct team folder. It turns a multi-step manual setup into a single-command automated workflow.

Setup guide

Set up Descript 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 Descript 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: "descript-mcp-client",
  servers: {
    "descript-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Descript MCP in Mastra AI

You define a workflow step using `create_transcription` and configure Mastra's automatic retry policy. If the Descript API hiccups, Mastra retries the step with exponential backoff before failing.

Yes. Your agent can call `list_templates` to view available layouts, then use that data to structure new projects. This lets you automate consistent video formatting across your entire team.

You initialize the client pointing to the secure server URL. Mastra AI automatically discovers the MCP tools, allowing you to spread them directly into your agent's toolset.

Yes. Mastra supports human-in-the-loop workflows. You can configure the agent to pause and ask for approval before it invokes `create_export` on your project.

Only your local Mastra AI instance. The server acts as a secure bridge, passing your project data and transcriptions directly to your agent without routing them through third-party servers.

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