How to Use the AssemblyAI MCP in Mastra AI

Q: How do I extract chapters from a podcast in AssemblyAI and Mastra AI?

Add getchapters to a secondary agent in your workflow. It waits for the primary transcription to finish and then chunks the text into logical segments.

Build fault-tolerant audio processing workflows in Mastra AI using AssemblyAI tools.

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Connect AssemblyAI MCP to Mastra AI

Create your Vinkius account to connect AssemblyAI 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 AssemblyAI with Mastra AI

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Automate audio pipelines with the Mastra AI MCP Server

Trigger `transcribe_audio_url` within a Mastra workflow step. If the audio host times out, the framework automatically retries the request with exponential backoff. You string these tools together to build massive content engines. One step pulls the audio, the next step waits for completion, and a final step runs `get_summary` to email the results.

Branch logic based on audio sentiment

Feed the output of `get_sentiments` into a conditional router. Your agent evaluates the emotional tone of a customer service call and decides which department gets the escalation ticket. Highly negative calls trigger immediate alerts. Neutral calls just get logged using `get_topics` to categorize the discussion for later review.

Manage transcript lifecycles automatically

Use `list_transcripts` to audit old processing jobs on a weekly schedule. The agent identifies outdated files and triggers `delete_transcript` to keep your storage costs down. This entire sequence runs without human input. You configure the tools in your Mastra Agent array and let the workflow engine handle the execution state.

Setup guide

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

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

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

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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 Mastra AI

Initialize a new MCPClient with your endpoint URL. Call listTools() and spread that array directly into your agent configuration.

Enable requireToolApproval on the transcription tools. The workflow halts before submitting the audio URL, letting a manager verify the source first.

The framework auto-detects between Streamable HTTP or SSE. You just provide the Vinkius URL and Mastra handles the underlying connection.

Add get_chapters to a secondary agent in your workflow. It waits for the primary transcription to finish and then chunks the text into logical segments.

Vinkius runs the tools inside a zero-trust sandbox. The audio URLs and resulting text strings exist only during the execution window before the container terminates.

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