How to Use the QingFlow MCP in Mastra AI

Q: Can Mastra AI manage actions across multiple QingFlow applications?

Yes, the framework handles cross-app logic by combining listdata from one app with createrecord in another. Mastra's workflow engine manages the state transitions between these distinct applications.

Build resilient, multi-step BPM workflows using Mastra AI and the QingFlow MCP server.

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Connect QingFlow MCP to Mastra AI

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Setup QingFlow with Mastra AI

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Mastra AI Conditional Approval Pipelines

The `get_workflow_status` tool allows Mastra AI agents to monitor active approval chains and trigger secondary code paths based on the current state. If a record stalls in a pending queue, your Mastra workflow automatically shifts gears. You can program the agent to run `list_users` to find an alternative manager, then use `update_record` to reassign the task. This programmatic routing keeps business processes moving without requiring manual human intervention.

Automated Error Recovery for Record Creation

Executing `create_record` through Mastra AI guarantees that database insertion failures are met with immediate, structured retries. The framework uses exponential backoff to handle transient network issues when writing to QingFlow. If the write fails repeatedly, Mastra runs a fallback step to log the payload locally and alerts the admin team. This prevents data loss when importing high volumes of business records into your BPM application.

Multi-App Schema Synchronization

Your Mastra agent calls `get_app_schema` to inspect the structure of multiple QingFlow apps before running sync operations via the MCP server. This step ensures that data mapped from external databases matches the exact field types expected by the destination app. If a schema mismatch occurs, the agent uses `list_apps` to verify if a compatible application exists elsewhere in the workspace. This automated validation saves hours of debugging broken API integrations.

Setup guide

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

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

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

Mastra AI catches update failures by monitoring the output of `update_record`. It then uses its built-in retry engine to execute the change again, or routes the request to an error-handling workflow if the failure persists.

Yes, you can configure Mastra AI to pause whenever the agent calls `delete_record`. The workflow engine holds the operation until an administrator manually verifies the deletion request.

You deploy the agent to your cloud provider using the Mastra CLI after configuring the MCP setup. The agent connects to the MCP server endpoint to execute tools like `list_workflows` autonomously.

Yes, the framework handles cross-app logic by combining `list_data` from one app with `create_record` in another. Mastra's workflow engine manages the state transitions between these distinct applications.

Your workflow status logs and record details stay within your secure VPC or cloud instance. Vinkius handles the MCP server execution in a zero-trust sandbox, ensuring no raw data is stored or leaked during tool execution.

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