How to Use the Mingdao Cloud MCP in Mastra AI

Q: Can I require admin approval before deleting Mingdao Cloud rows in Mastra AI?

Yes, you set requireToolApproval to true for the deleterow tool in your agent configuration. This stops the workflow until a human signs off on the deletion.

Q: How does Mastra AI discover the schema of a Mingdao Cloud worksheet?

The agent calls getworksheetschema through the MCP Server. This returns the field IDs and types, allowing the agent to construct valid payloads for new records.

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Automate worksheet updates with Mastra AI agents

The `update_row` tool allows your Mastra AI agent to modify existing database records based on workflow conditions. You define this logic within the MCP Server configuration. Mapping this tool alongside `get_row_details` lets you build self-healing pipelines. The agent reads the current state, checks for discrepancies, and applies the necessary changes without manual intervention.

Run safe row deletions via the MCP Server

The `delete_row` tool removes specific entries from your Mingdao Cloud worksheets during automated cleanups. To prevent accidental data loss, you configure Mastra AI to require human-in-the-loop approval before executing this destructive action. This setup pairs well with `list_rows` to identify stale or duplicate records. The agent flags the targets, and the workflow pauses until an administrator approves the deletion.

Map Mingdao Cloud structures inside Mastra AI

The `get_app_info` tool retrieves the structure of your target application to feed your agent's context. This allows Mastra AI to understand the context of the worksheets it is manipulating. By combining this with `get_worksheet_schema`, your workflows adapt automatically when users modify fields in the zero-code platform. Your agent reads the new schema and adjusts its data payloads dynamically.

Setup guide

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

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

const result = await agent.generate(
  "List recent Mingdao Cloud transactions"
);
console.log(result.text);

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Common questions about Mingdao Cloud MCP in Mastra AI

You use the built-in workflow engine to catch errors from the `update_row` tool. Mastra AI retries the call automatically using exponential backoff.

Yes, you set `requireToolApproval` to true for the `delete_row` tool in your agent configuration. This stops the workflow until a human signs off on the deletion.

The agent calls `get_worksheet_schema` through the MCP Server. This returns the field IDs and types, allowing the agent to construct valid payloads for new records.

External webhooks can trigger a Mastra AI workflow that queries the database using `list_rows` through the MCP Server, branching based on the results.

This MCP integration accesses worksheet schemas, row records, and user lists. Vinkius runs the connector inside a zero-trust sandbox, routing the API calls directly using your single secure endpoint token.

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