How to Use the Metabolic Energy Estimator MCP in Mastra AI

Q: How do I register the Metabolic Energy Estimator MCP Server tools within a Mastra AI agent?

Install @mastra/mcp@latest, initialize the client with the server URL, and call mcpClient.listTools(). You can then spread these tools directly into your Mastra agent configuration.

Q: Does the Metabolic Energy Estimator MCP Server support human-in-the-loop validation in Mastra AI?

Yes. You can configure requireToolApproval on the Mastra client to intercept calls to calculateweightlossprojection before the agent commits to a specific caloric deficit timeline.

Q: What formula does the TDEE tool use to calculate energy expenditure?

The calculatetdee tool uses the Mifflin-St Jeor equation. It combines weight, height, age, biological sex, and an activity multiplier to output both BMR and TDEE.

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Connect Metabolic Energy Estimator MCP to Mastra AI

Create your Vinkius account to connect Metabolic Energy Estimator 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 Metabolic Energy Estimator with Mastra AI

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Build resilient metabolic workflows in Mastra AI

`calculate_tdee` determines BMR and daily expenditure using the Mifflin-St Jeor formula, acting as the foundation for your agentic workflows. Mastra AI wraps this tool in its workflow engine, enabling conditional branching that adjusts caloric recommendations based on real-time activity changes. If a user logs an unexpectedly high activity level, Mastra routes the data through the TDEE tool and automatically triggers follow-up checks. The built-in retry mechanisms ensure that even network blips won't disrupt your automated coaching pipelines.

Run multi-step weight loss projections with this MCP Server

`calculate_weight_loss_projection` uses a deterministic 7,700 kcal per kilogram model to forecast body weight changes over time. Mastra AI executes this projection inside its state machine, allowing you to build complex multi-week plan adjustments without writing boilerplate logic. You can set up human-in-the-loop approvals using Mastra's tool validation. This prevents your agent from recommending calorie deficits that are too aggressive before a human coach signs off.

Automate exercise tracking via local catalogs

`search_activity_catalog` scans a local database of over 80 sports to find exact MET values without calling slow external APIs. Your Mastra agent can then pass the output to `estimate_calories_burned` to compute energy expenditure based on duration and body weight. Because Mastra handles transport protocols auto-magically, your agent can query this catalog via HTTP or SSE. The local execution keeps your automated calorie tracking loops fast and reliable.

Setup guide

Set up Metabolic Energy Estimator 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 Metabolic Energy Estimator 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: "metabolic-energy-estimator-mcp-client",
  servers: {
    "metabolic-energy-estimator-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Metabolic Energy Estimator MCP in Mastra AI

Install `@mastra/mcp@latest`, initialize the client with the server URL, and call `mcpClient.listTools()`. You can then spread these tools directly into your Mastra agent configuration.

Yes. Mastra AI features automatic retries with exponential backoff, ensuring your metabolic calculations and weight projections complete even during high-traffic spikes.

Yes. You can configure `requireToolApproval` on the Mastra client to intercept calls to `calculate_weight_loss_projection` before the agent commits to a specific caloric deficit timeline.

The `calculate_tdee` tool uses the Mifflin-St Jeor equation. It combines weight, height, age, biological sex, and an activity multiplier to output both BMR and TDEE.

Your weight, metabolic stats, and activity logs are processed entirely in memory within an isolated execution environment on our MCP Server. No data persists on the server, and Vinkius secures the endpoint token to block unauthorized access to your health metrics.

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