HealthTech & Life Sciences HooliSubmitted July 25, 2026

NutriKids: Agentic AI for Pediatric Nutrition

An MCP app on the Model Context Protocol built by Hooli at the Amrita University Coimbatore NitroStack × MCP To The Moon hackathon and deployed on NitroStack.

About this project

NutriKids is an Agentic AI-powered pediatric nutrition intelligence platform built using NitroStack's Model Context Protocol (MCP). Parents often struggle to obtain reliable, personalised guidance for concerns such as growth assessment, nutritional deficiencies, meal planning, and child health. Traditional AI chatbots typically rely on a single prompt, making it difficult to coordinate specialised healthcare knowledge across multiple domains. To address this, NutriKids introduces a Supervisor Agent that analyses each user query and dynamically orchestrates specialised MCPs based on the required expertise. The platform currently includes three MCPs: Growth MCP for WHO-based growth assessment, Medical MCP for symptom and nutritional deficiency analysis, and Food MCP for personalised meal planning and dietary recommendations. Each MCP independently performs its specialised reasoning, while the Supervisor Agent reconciles their outputs into a single structured, parent-friendly response. Built with NitroStack, the solution demonstrates a modular and scalable Agentic AI architecture where new healthcare capabilities can be added as independent MCPs without changing the existing system. By combining intelligent orchestration, evidence-based recommendations, and personalised nutrition guidance, NutriKids showcases how MCP can be applied to solve real-world healthcare challenges through collaborative AI agents rather than a single monolithic model. video - https://canva.link/8xmwfwfm6xp3fmg

HealthTech & Life Sciences track

Design AI-powered solutions for healthcare, diagnostics, patient care, medical research, and life sciences.

Team Hooli

  • Pavan Vignesh VeluriLead

  • Dinesh Veera Bhargav Akula

  • Damarapati Pavan Krishna

  • Abhiram bikkina

Frequently asked questions

What does NutriKids: Agentic AI for Pediatric Nutrition do?
NutriKids is an Agentic AI-powered pediatric nutrition intelligence platform built using NitroStack's Model Context Protocol (MCP). Parents often struggle to obtain reliable, personalised guidance for concerns such as growth assessment, nutritional deficiencies, meal planning, and child health. Traditional AI chatbots typically rely on a single prompt, making it difficult to coordinate specialised healthcare knowledge across multiple domains. To address this, NutriKids introduces a Supervisor Agent that analyses each user query and dynamically orchestrates specialised MCPs based on the required expertise. The platform currently includes three MCPs: Growth MCP for WHO-based growth assessment, Medical MCP for symptom and nutritional deficiency analysis, and Food MCP for personalised meal planning and dietary recommendations. Each MCP independently performs its specialised reasoning, while the Supervisor Agent reconciles their outputs into a single structured, parent-friendly response. Built with NitroStack, the solution demonstrates a modular and scalable Agentic AI architecture where new healthcare capabilities can be added as independent MCPs without changing the existing system. By combining intelligent orchestration, evidence-based recommendations, and personalised nutrition guidance, NutriKids showcases how MCP can be applied to solve real-world healthcare challenges through collaborative AI agents rather than a single monolithic model. video - https://canva.link/8xmwfwfm6xp3fmg
Who built NutriKids: Agentic AI for Pediatric Nutrition?
NutriKids: Agentic AI for Pediatric Nutrition was built by team Hooli at the Amrita University Coimbatore NitroStack × MCP To The Moon hackathon, in the HealthTech & Life Sciences track.
What is an MCP app and how is it built?
An MCP app is an application built on the Model Context Protocol — an open standard that lets AI agents connect to tools, data, and APIs. This project exposes MCP tools and resources that agentic AI systems can call. It was built and deployed on NitroStack, the full-stack platform for shipping MCP apps and servers.