How to Use the UnifyApps MCP in Mastra AI

Q: How do I check flow history using UnifyApps and Mastra AI?

You call the listflowexecutions tool. This provides the execution history needed to build logic around retries, letting your agent framework know if it needs to try a payment method again.

Q: Does UnifyApps support listing all configured integrations with Mastra AI?

Yes, you use listintegrations. This gives the full inventory of services connected to your workflow engine. It's crucial for knowing what alternatives exist if one step fails.

Q: What kind of credentials does this MCP Server touch for UnifyApps and Mastra AI?

This server deals with connection details. Specifically, listactiveconnections allows your agent to check the current status of account connections before executing a sensitive step.

Q: Can I list all defined automation workflows using UnifyApps and Mastra AI?

You use listautomationflows. This retrieves every flow definition, which is necessary for your agent to model the entire dependency graph of a complex operation.

Q: If I need to check agent setup details, which MCP Server function do I use with UnifyApps and Mastra AI?

The listaiagents tool lists all configured agents in the UnifyApps environment. This allows your framework to build conditional branching based on available resources.

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Monitor Workflow Status via MCP Server

Use `list_flow_executions` to check the history of any automated process. This is key for building workflows that need to handle failure gracefully, so you can confirm exactly when a retry happened. Don't forget `list_automation_flows`. You can pull all flow definitions, which lets your agent framework build complex execution trees and manage dependencies.

Audit Connections on the Fly

The tool `list_active_connections` lists every account connection. This is essential for your multi-step workflows because you need to verify credentials before attempting a sensitive action. When building failure handling, `list_integrations` lets your agent look across all configured services to determine which fallback methods are available.

Discover Agent and Integration Details

To manage the agents involved in complex flows, run `list_ai_agents`. This gives you a list of every specialized AI agent defined within UnifyApps. Your framework can then select the right agent for branching logic. Need to know what an integration does? Call `get_integration_details` to get specific operational parameters.

Setup guide

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

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

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

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Common questions about UnifyApps MCP in Mastra AI

You call the `list_flow_executions` tool. This provides the execution history needed to build logic around retries, letting your agent framework know if it needs to try a payment method again.

Yes, you use `list_integrations`. This gives the full inventory of services connected to your workflow engine. It's crucial for knowing what alternatives exist if one step fails.

This server deals with connection details. Specifically, `list_active_connections` allows your agent to check the current status of account connections before executing a sensitive step.

You use `list_automation_flows`. This retrieves every flow definition, which is necessary for your agent to model the entire dependency graph of a complex operation.

The `list_ai_agents` tool lists all configured agents in the UnifyApps environment. This allows your framework to build conditional branching based on available resources.

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