How to Use the YMovE Fitness MCP in Mastra AI

Q: Can YMovE Fitness generate a full meal plan using Mastra AI?

Yes. You can call generatemealplan within a multi-step workflow. If the initial calorie calculation fails, the system automatically retries with different parameters until it gets a solid result.

Q: What if I need to search recipes using Mastra AI?

You can use searchrecipes and build robust workflows around it. If one dietary filter fails, the workflow automatically attempts another valid category, ensuring you always find matching options.

Q: Does YMovE Fitness support complex program generation with Mastra AI?

Totally. You can define a multi-step process using generateprogram and build in conditional logic—for example, if the user is a beginner, it retries with fewer exercises.

Q: Can I list all available muscle groups using Mastra AI?

Sure thing. The agent can call listmusclegroups to ensure your workout generation logic always uses valid anatomical terms and doesn't break due to outdated data.

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Connect YMovE Fitness MCP to Mastra AI

Create your Vinkius account to connect YMovE Fitness 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 YMovE Fitness with Mastra AI

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Program Generation Reliability on Mastra AI

Building a complex workout regimen? Use `generate_program` to create multi-week plans, and let the Mastra AI workflow engine handle retries if the initial call fails. It builds reliable fitness agents that don't just quit when things get tricky. This framework is designed for processes that *must* succeed, ensuring your users always get a complete training program even if an external service hiccups.

Nutrition Planning with Mastra AI MCP Server

Generating meals requires precision. You can use `generate_meal_plan` to target specific calorie goals within a workflow. If the first attempt fails, Mastra automatically retries or switches methods, guaranteeing a usable plan. This makes your fitness application extremely dependable; you don't have to worry about flaky API calls messing up the user experience.

Workout Search and Detail Retrieval on Mastra AI

When a user needs today’s routine, the `generate_workout` tool can be wrapped in complex logic. If one search fails, your agent knows how to fall back—maybe it tries `search_exercises` first before attempting full generation. It handles conditional branching perfectly, letting you build sophisticated fitness flows that adapt on the fly.

Setup guide

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

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

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

The server primarily touches nutritional data related to UPC/EAN barcodes. Because of the framework's built-in retry and failure handling, you get reliable access without exposing unnecessary user details.

Yes. You can call `generate_meal_plan` within a multi-step workflow. If the initial calorie calculation fails, the system automatically retries with different parameters until it gets a solid result.

You can use `search_recipes` and build robust workflows around it. If one dietary filter fails, the workflow automatically attempts another valid category, ensuring you always find matching options.

Totally. You can define a multi-step process using `generate_program` and build in conditional logic—for example, if the user is a beginner, it retries with fewer exercises.

Sure thing. The agent can call `list_muscle_groups` to ensure your workout generation logic always uses valid anatomical terms and doesn't break due to outdated data.

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