How to Use the Gelato MCP in Mastra AI

Build reliable print-on-demand workflows with Mastra AI and this managed MCP Server.

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Connect Gelato MCP to Mastra AI

Create your Vinkius account to connect Gelato 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 Gelato with Mastra AI

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Claude

Perplexity

Automated order submission logic

Chain `create_print_order` within your Mastra workflows to handle complex fulfillment tasks. If an order fails, the agent can retry the operation based on your defined logic. This setup removes manual intervention for standard print jobs. You define the sequence once and let the agent manage the execution flow.

Conditional shipping cost routing

Use `get_shipping_quote` to branch your workflow based on price thresholds. If a quote exceeds your limit, the agent can trigger an alert or select a cheaper carrier. Everything happens inside the agent's decision loop. You get programmatic control over fulfillment costs without writing custom polling scripts.

Proactive shipment monitoring

Deploy an agent to poll `get_order_shipments` and notify your team of delays. The workflow engine handles the timing and logic for these checks automatically. It keeps your operations running smoothly. You don't need to build custom cron jobs to track your print-on-demand status updates.

Setup guide

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

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

const result = await agent.generate(
  "List recent Gelato 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 Gelato. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Real-time monitoring

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visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Gelato MCP in Mastra AI

Add the server URL to your MCP client config in Mastra. The framework automatically detects and exposes the tools for your agents.

Mastra provides built-in retry logic for agents. If a tool call fails, the framework handles the backoff strategy automatically.

Absolutely. You can define multi-step processes where agents check, quote, and submit orders without human input.

You can toggle manual approval for any tool call. This forces the agent to wait for your sign-off before placing an order.

The server only processes your specific print-on-demand metadata. All communication between your agent and the API remains strictly isolated in your instance.

Use it with your favorite AI tools

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