How to Use the EZO Asset Intelligence MCP in Mastra AI

Q: How do I initialize the EZO Asset Intelligence MCP client in Mastra AI?

Install the package using npm install @mastra/mcp@latest. Instantiate the MCPClient with your Vinkius server URL, then call mcpClient.listTools() to spread the EZO tools directly into your Mastra agent configuration.

Q: Can I require manual approval before Mastra AI queries EZO Asset Intelligence?

Yes. Mastra AI supports requireToolApproval, which lets you halt the workflow before the agent runs tools like listaccountmembers or accesses sensitive user details.

Q: How does Mastra AI handle EZO Asset Intelligence API rate limits?

Mastra's workflow engine has native retry mechanisms. If listmanagedassets hits a rate limit, the engine pauses and retries with exponential backoff until the EZO API responds.

Run automated, self-healing workflows with Mastra AI and the EZO Asset Intelligence MCP Server.

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Connect EZO Asset Intelligence MCP to Mastra AI

Create your Vinkius account to connect EZO Asset Intelligence 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 EZO Asset Intelligence with Mastra AI

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Run resilient EZO audits using Mastra workflows

This integration uses `quick_asset_volume_audit` and `list_consumable_inventory` to run scheduled checks on your physical EZO stock levels within Mastra workflows. If the EZO API experiences temporary downtime, Mastra AI uses its built-in exponential backoff to retry the audit automatically. You can build a Mastra workflow that triggers every Friday afternoon to pull these EZO counts. The Mastra agent gathers the numbers, checks for discrepancies, and alerts your team without manual intervention.

Build automated recovery steps with Mastra AI

The server relies on `list_overdue_checkouts` and `list_account_members` to power conditional branching workflows in Mastra when equipment is late. When Mastra AI detects an overdue laptop, it branches to lookup the member's contact info and triggers a notification. You can set up a human-in-the-loop step in Mastra AI using `requireToolApproval` before any EZO checkout notification is sent. This ensures your operations team can double-check the physical shelf before the Mastra agent emails the employee.

Route equipment requests via this MCP Server

This server exposes `list_available_assets` and `get_asset_detailed_data` so Mastra agents can locate and verify gear for new hires. The Mastra workflow matches the hardware requirements of an incoming staff member with the physical EZO inventory. If the exact laptop model isn't available, Mastra's workflow engine branches to check alternative locations. The Mastra agent checks the EZO asset details, logs the match, and prepares the checkout record.

Setup guide

Set up EZO Asset Intelligence 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 EZO Asset Intelligence 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: "ezo-asset-intelligence-mcp-client",
  servers: {
    "ezo-asset-intelligence-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent EZO Asset Intelligence 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 EZO Asset Intelligence. 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 EZO Asset Intelligence MCP in Mastra AI

Install the package using `npm install @mastra/mcp@latest`. Instantiate the `MCPClient` with your Vinkius server URL, then call `mcpClient.listTools()` to spread the EZO tools directly into your Mastra agent configuration.

Yes. Mastra AI supports `requireToolApproval`, which lets you halt the workflow before the agent runs tools like `list_account_members` or accesses sensitive user details.

Mastra's workflow engine has native retry mechanisms. If `list_managed_assets` hits a rate limit, the engine pauses and retries with exponential backoff until the EZO API responds.

Yes. Mastra automatically detects the transport type, allowing you to connect to the EZO MCP Server on Vinkius using either Streamable HTTP or Server-Sent Events without manual configuration.

Your credentials stay locked inside Vinkius's zero-trust V8 sandbox. Mastra AI only interacts with the secure MCP endpoint, meaning your physical asset logs and employee directories are never stored on external workflow servers.

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