How to Use the ElevenLabs MCP in Mastra AI

Q: Can I use ElevenLabs pronunciation dictionaries inside Mastra AI agents?

Yes. Mastra AI agents can fetch active lexicons using listpronunciationdictionaries to correct industry jargon before generating the final audio output.

Q: How do I track ElevenLabs subscription limits inside Mastra AI workflows?

You can insert a step in your workflow that calls getsubscription and getuserinfo. If the remaining characters drop below a threshold, the workflow sends an automated alert to your admin.

Build resilient voice workflows in Mastra AI with ElevenLabs audio tools.

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Connect ElevenLabs MCP to Mastra AI

Create your Vinkius account to connect ElevenLabs 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 ElevenLabs with Mastra AI

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Resilient audio generation workflows

Mastra AI workflows handle failures gracefully when invoking this MCP. When your voice generation step fails, the workflow engine automatically retries `text_to_speech` using exponential backoff to handle temporary API hiccups. If a specific model is offline, your workflow can query `list_models` to fall back to a different synthesis model. This keeps your automated pipelines running without manual intervention.

Automated voice auditing and history sync

Keep your external databases in sync with your actual usage. Mastra AI agents use `list_history` and `get_history_item` to pull past generations and log them in your local database. This makes auditing simple. You can track exactly which agent generated which audio file, matching project IDs from `list_projects` to your internal client billing records.

Dynamic pronunciation adjustments in pipelines

Brand names and technical terms often break standard text-to-speech engines. Your Mastra AI agents can query `list_pronunciation_dictionaries` to ensure the correct lexicon is applied during execution. You can dynamically inspect the voice profiles using `get_voice` before running the pipeline. This ensures your automated output always matches the target brand guidelines.

Setup guide

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

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

const result = await agent.generate(
  "List recent ElevenLabs 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 ElevenLabs. 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 ElevenLabs MCP in Mastra AI

Mastra AI uses its built-in workflow engine to catch errors from `text_to_speech`. If a call fails, it triggers automatic retries or falls back to an alternative voice fetched via `list_voices`.

Yes. Mastra AI agents can fetch active lexicons using `list_pronunciation_dictionaries` to correct industry jargon before generating the final audio output.

You can insert a step in your workflow that calls `get_subscription` and `get_user_info`. If the remaining characters drop below a threshold, the workflow sends an automated alert to your admin.

Yes. You can track your translation and dubbing pipelines by calling `list_projects` to monitor progress across different localized assets.

Yes. Vinkius isolates this MCP Server inside a zero-trust environment. Your sensitive API credentials and subscription details retrieved via `get_subscription` are never logged or exposed to external networks.

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