How to Use the Ship24 MCP in Mastra AI

Q: Can I build multi-step processes with Ship24 and the Mastra AI?

Yes, you define the sequence. For example, Step 1: Check getapistatus. Step 2: If good, call createtracker. Step 3: If tracking fails, notify admin.

Q: Does Ship24 support tracking multiple carriers within one workflow using Mastra AI?

It does. Your workflows can iterate through listcouriers to check status across different types of services, making sure you cover all bases before declaring success.

Q: What kind of data does the Ship24 MCP Server touch regarding tracking numbers?

It manages the lifecycle data: initial lookup via findtrackerbynumber, status changes, and updated metadata for specific shipment tracking numbers.

Build failure-proof logistics workflows for your AI agent client.

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Connect Ship24 MCP to Mastra AI

Create your Vinkius account to connect Ship24 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 Ship24 with Mastra AI

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Verify Carrier Connectivity Status

Start any workflow by calling `get_api_status`. This checks the live connectivity to global carriers, letting you confirm before your multi-step process even starts. If the status is bad, your agent can immediately fail gracefully or reroute. It's a critical first step for complex business logic.

Manage Complex Tracking Workflows

The `get_tracking_results` tool gives you the current package status needed for conditional branching. Your agent can check if the status is 'Delivered' or 'Exception,' and then execute a totally different follow-up action. This allows your workflow to decide what happens next—like notifying an admin only if tracking fails three times.

Update Tracker Metadata Programmatically

Use `update_tracker_info` when a shipment requires manual data correction, like fixing a recipient address. Your agent updates the records and continues the workflow from there. This is essential for handling exceptions where simple tracking isn't enough; you gotta fix the record first.

Setup guide

Set up Ship24 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 Ship24 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: "ship24-mcp-client",
  servers: {
    "ship24-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Ship24 Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Ship24 tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Ship24 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 Ship24. 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 Ship24 MCP in Mastra AI

The MCP Server is designed for workflows that expect failure. You set up conditional branches: if tracking fails, your agent automatically retries using a different method or waits and tries again.

Yes, you define the sequence. For example, Step 1: Check `get_api_status`. Step 2: If good, call `create_tracker`. Step 3: If tracking fails, notify admin.

Because your workflows are designed with failure handling in mind, they won't just break. The agent can detect the error and execute a defined fallback plan instead of stopping dead.

It does. Your workflows can iterate through `list_couriers` to check status across different types of services, making sure you cover all bases before declaring success.

It manages the lifecycle data: initial lookup via `find_tracker_by_number`, status changes, and updated metadata for specific shipment tracking numbers.

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