How to Use the Wellhub MCP in Mastra AI

Q: What is the best way to list available classes with Wellhub using Mastra AI?

You can wrap listclasses inside a multi-step process. This lets you check capacity, then filter based on corporate membership rules, all within one reliable workflow.

Build reliable, multi-step Wellhub workflows with Mastra AI.

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Connect Wellhub MCP to Mastra AI

Create your Vinkius account to connect Wellhub 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 Wellhub with Mastra AI

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Process Check-ins and Eligibility Checks

You can build a workflow that first calls `check_eligibility` to determine access. If the employee is eligible, the next step validates their visit using `validate_check_in`. The agent handles the entire sequence. If `validate_check_in` fails because of an expired plan, Mastra AI automatically routes the process to notify an administrator instead of failing entirely.

Manage Bookings and Schedules

Design a workflow that checks both current bookings (`list_bookings`) and available slots using `list_classes`. You can set up conditional logic: if no spots are found, notify the user to try another day. This handles complex scheduling needs. Mastra AI ensures that even if one API call times out, the entire workflow retries gracefully.

Retrieve Detailed Employee Lists

The agent can build a multi-step process to get a complete list of corporate employees via `list_eligible_employees`. It checks the plan tier and usage status for every record. If the initial API call fails, Mastra AI's built-in exponential backoff retries the request until it succeeds or notifies you with clear failure context.

Setup guide

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

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

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

Mastra AI uses a built-in workflow engine that supports conditional branching. You don't just run single tools; you build sequences that handle failure states, like retrying `get_partner_info` if the initial connection drops.

Absolutely. The framework automatically supports retries with exponential backoff. This means if a call to list partner locations fails, it doesn't just crash—it tries again intelligently.

You handle operational data like plan tiers, booking statuses, and check-in records. The workflow engine manages the flow between these different API results to complete a business task.

You can wrap `list_classes` inside a multi-step process. This lets you check capacity, then filter based on corporate membership rules, all within one reliable workflow.

It touches employee plan tiers, booking history, and real-time gym check-in records. Mastra AI makes sure you can reliably read and act on all these operational details.

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