How to Use the SuperSaaS MCP in Mastra AI

Q: How does SuperSaaS integrate with mastra-ai for booking?

You build a conditional workflow. For instance, first call getschedule to verify time slots; if successful, then run createappointment. This ensures bookings only happen when the schedule is confirmed.

Q: Can I use SuperSaaS with mastra-ai for complex billing logic?

Yes. You can design a sequence: Check balance using getaccountbalance, and if it passes, proceed to run the booking tools. If the payment fails at any step, the agent automatically handles retries.

Q: What if a SuperSaaS booking fails using mastra-ai?

The framework handles it. If createappointment fails, the agent doesn't just stop; it can execute predefined compensating actions, like notifying an admin or retrying later.

Build reliable workflows with SuperSaaS: Automate complex booking logic using mastra-ai.

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Atomic Booking and Validation Flows

The `create_appointment` tool initiates a booking, but you should wrap this in a workflow that first checks funds. Before creating the appointment, use `get_account_balance`. If the balance is low, the mastra-ai agent can automatically trigger a notification instead of failing. You'll build reliable multi-step logic: Check Balance -> Get Schedule -> Create Appointment.

Managing State Changes and Cancellations

When an appointment needs to be removed, call `delete_appointment`. The workflow engine handles the success or failure of this deletion. You can then automatically run `list_changes` immediately after to log that action for auditing. Need to change a booking? Use `update_appointment` inside your sequence; if the update fails (maybe due to conflicting times), mastra-ai can retry it later with exponential backoff.

Complex User and Schedule Retrieval

You don't just need one user record. Start by calling `list_account_users` to get a list, then loop through that list using `get_user` for each entry. This builds complex data structures needed for full system checks. Similarly, use `list_schedules` to find all available scheduling options before your main workflow begins.

Setup guide

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

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

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

You build a conditional workflow. For instance, first call `get_schedule` to verify time slots; if successful, then run `create_appointment`. This ensures bookings only happen when the schedule is confirmed.

Yes. You can design a sequence: Check balance using `get_account_balance`, and if it passes, proceed to run the booking tools. If the payment fails at any step, the agent automatically handles retries.

It's built for that. The workflow engine allows you to connect multiple tool calls—like checking availability and then creating an appointment—into one reliable, stateful process.

The framework handles it. If `create_appointment` fails, the agent doesn't just stop; it can execute predefined compensating actions, like notifying an admin or retrying later.

The server handles user accounts and financial balances. The `get_account_balance` tool is key here, allowing your workflows to check the current account credit balance before taking action.

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