How to Use the Cartesia (Voice AI) MCP in Mastra AI

Q: How do I configure Cartesia (Voice AI) in Mastra AI?

Initialize new MCPClient with your endpoint URL. Call mcpClient.listTools() and spread the results into your agent's tool array.

Q: Can I require human approval for Cartesia (Voice AI) in Mastra AI?

Yes. Set requireToolApproval on destructive actions like deleting a voice dictionary, keeping a human in the loop.

Build resilient voice workflows with Cartesia and Mastra AI, handling audio cloning with automatic retries.

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Connect Cartesia (Voice AI) MCP to Mastra AI

Create your Vinkius account to connect Cartesia (Voice AI) 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 Cartesia (Voice AI) with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Reliable batch transcription

Audio processing fails. Networks drop. Mastra AI wraps the `stt_batch` tool in a workflow engine that automatically retries the request when things break. Passing gigabytes of audio to the endpoint works without worrying about timeouts. The framework handles the exponential backoff while the transcription runs.

Automated Mastra AI voice management

Managing hundreds of custom voices gets messy fast. Your workflow can query `list_voices` and automatically clear out old profiles using `delete_voice`. This MCP Server also lets you track exactly how much you spend. Call `get_usage_credits` at the end of a run to log the exact billing impact of your voice generation.

Audio editing and infill

Stitching audio clips together usually leaves harsh cuts. The `infill_bytes` tool generates the exact transitional audio needed to connect two distinct segments smoothly. Mapping a new voice over existing audio works through `voice_changer_bytes`. Intonation stays exactly the same, but the speaker changes completely.

Setup guide

Set up Cartesia (Voice AI) 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 Cartesia (Voice AI) 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: "cartesia-voice-ai-mcp-client",
  servers: {
    "cartesia-voice-ai-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Cartesia (Voice AI) MCP in Mastra AI

Initialize `new MCPClient` with your endpoint URL. Call `mcpClient.listTools()` and spread the results into your agent's tool array.

That is the whole point of this framework. Mastra handles automatic retries with exponential backoff if a heavy transcription job drops.

Spread the MCP tools into your agent. The framework's conditional branching lets you clone a voice, verify it, and then immediately generate speech.

Yes. Set `requireToolApproval` on destructive actions like deleting a voice dictionary, keeping a human in the loop.

Zero-trust architecture protects your inputs. When your workflow passes `.wav` files or pronunciation rules through the MCP server, they stay entirely ephemeral.

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