Metabolic Energy Estimator MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 4 tools to Calculate Tdee, Calculate Weight Loss Projection, Estimate Calories Burned, and more
GDPR Free for SubscribersThe Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Metabolic Energy Estimator through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
Ask AI about this MCP Server for Vercel AI SDK
The Metabolic Energy Estimator MCP Server for Vercel AI SDK is a standout in the Data Analytics category — giving your AI agent 4 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Metabolic Energy Estimator, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Metabolic Energy Estimator MCP Server
Autonomous health and fitness agents demand uncompromising metabolic accuracy. When standard LLMs attempt to estimate calories burned for a specific activity, they guess wildly. The Metabolic Energy Estimator MCP empowers your AI Agent by delegating this logic to a deterministic engine utilizing scientifically validated MET (Metabolic Equivalent of Task) values.
The Vercel AI SDK gives every Metabolic Energy Estimator tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 4 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
Core Capabilities
- Agentic Calorie Estimation: Search a native, offline catalog of over 80 specific physical activities and calculate exact calories burned based on the user's exact weight and duration.
- TDEE & BMR Engine: Implements the rigorous Mifflin-St Jeor equation to establish the user's Basal Metabolic Rate and Total Daily Energy Expenditure without sending health metrics to the cloud.
- Weight Loss Projection: Compute the exact number of days and weeks required to hit a target weight given a precise daily caloric deficit, complete with safety warnings.
The Metabolic Energy Estimator MCP Server exposes 4 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 4 Metabolic Energy Estimator tools available for Vercel AI SDK
When Vercel AI SDK connects to Metabolic Energy Estimator through Vinkius, your AI agent gets direct access to every tool listed below — spanning metabolic-calculation, fitness-tracking, tdee, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Calculate tdee on Metabolic Energy Estimator
Calculates Total Daily Energy Expenditure (TDEE) and Basal Metabolic Rate (BMR) using the Mifflin-St Jeor equation
Calculate weight loss projection on Metabolic Energy Estimator
1kg of fat = 7700 calories. Projects how many days and weeks it will take to reach a target weight based on a daily calorie deficit
Estimate calories burned on Metabolic Energy Estimator
You MUST provide an activityId found via search_activity_catalog. Calculates exactly how many calories are burned doing a specific physical activity based on weight and time
Search activity catalog on Metabolic Energy Estimator
Searches the deterministic local catalog for activities and their exact MET values
Connect Metabolic Energy Estimator to Vercel AI SDK via MCP
Follow these steps to wire Metabolic Energy Estimator into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the Metabolic Energy Estimator MCP Server
Vercel AI SDK provides unique advantages when paired with Metabolic Energy Estimator through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Metabolic Energy Estimator integration everywhere
Built-in streaming UI primitives let you display Metabolic Energy Estimator tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Metabolic Energy Estimator + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Metabolic Energy Estimator MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Metabolic Energy Estimator in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Metabolic Energy Estimator tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Metabolic Energy Estimator capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Metabolic Energy Estimator through natural language queries
Example Prompts for Metabolic Energy Estimator in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Metabolic Energy Estimator immediately.
"I weigh 80kg and ran moderately for 45 minutes. How many calories did I burn?"
"I am a 30-year-old male, 180cm, 85kg, with a sedentary lifestyle. What is my TDEE?"
"I weigh 90kg and want to reach 80kg with a 500 calorie daily deficit. How long will it take?"
Troubleshooting Metabolic Energy Estimator MCP Server with Vercel AI SDK
Common issues when connecting Metabolic Energy Estimator to Vercel AI SDK through Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpMetabolic Energy Estimator + Vercel AI SDK FAQ
Common questions about integrating Metabolic Energy Estimator MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Explore More MCP Servers
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