HealthTech & Life Sciences INIT MINDSSubmitted July 26, 2026

MedGuard - an ai that assists patients

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

About this project

This project, MedGuard App, is a clinical medication safety evaluation server built on the NitroStack Model Context Protocol (MCP) framework. It acts as an intelligent assistant to help healthcare professionals and AI models cross-reference proposed medications against patients' medical histories. Here is a summary of the project's architecture and capabilities: 🛠️ Core Technology Stack Framework: NitroStack (@nitrostack/core and @nitrostack/cli) using TypeScript and Zod schema validation. Database: PostgreSQL / Supabase integration (@supabase/supabase-js, pg client) with automatic fallback to local JSON fixtures (patients.json & medguard-dataset.json). Development Tooling: Configured with tsx for script execution and TypeScript compiling. 🛡️ Key Features & Tools 1. Medication Safety Evaluation (medguard.tools.ts) evaluate_treatment_safety: Cross-checks a proposed drug (e.g., dermatology drug) against a patient's profile. Checks for drug-disease or drug-drug contraindications. Identifies severity/risk level (High, Medium, Low). Triggers CRITICAL warnings if the risk is high and the patient's kidney function (eGFR < 60) is compromised. Returns alternative treatments if safety thresholds are breached. get_patient_details: Fetches clinical metrics (conditions, eGFR, active medication list) for a patient. add_patient: Inserts a new patient record into either the live Supabase database or the local fallback cache. list_interaction_rules: Allows searching the dataset of clinical interaction rules. 2. Database & Schema Initialization (database.tools.ts) setup_medguard_database: Automates table creation and seeds initial patient/interaction rules into Supabase/PostgreSQL using supabase-schema.sql . Supabase Schema: Exposes the database structure as an MCP Resource. 3. Standardized Workflows & Prompts process_patient_workflow: A prompt template guiding the agent to verify patients, safely add new ones, inspect active drugs, and perform the safety evaluation. medguard_q

HealthTech & Life Sciences track

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

Source code

Team INIT MINDS

  • Kavin PrasathLead

  • Shoumik R S

  • Jayasuriyan R

  • Vidurvarshan

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Frequently asked questions

What does MedGuard - an ai that assists patients do?
This project, MedGuard App, is a clinical medication safety evaluation server built on the NitroStack Model Context Protocol (MCP) framework. It acts as an intelligent assistant to help healthcare professionals and AI models cross-reference proposed medications against patients' medical histories. Here is a summary of the project's architecture and capabilities: 🛠️ Core Technology Stack Framework: NitroStack (@nitrostack/core and @nitrostack/cli) using TypeScript and Zod schema validation. Database: PostgreSQL / Supabase integration (@supabase/supabase-js, pg client) with automatic fallback to local JSON fixtures (patients.json & medguard-dataset.json). Development Tooling: Configured with tsx for script execution and TypeScript compiling. 🛡️ Key Features & Tools 1. Medication Safety Evaluation (medguard.tools.ts) evaluate_treatment_safety: Cross-checks a proposed drug (e.g., dermatology drug) against a patient's profile. Checks for drug-disease or drug-drug contraindications. Identifies severity/risk level (High, Medium, Low). Triggers CRITICAL warnings if the risk is high and the patient's kidney function (eGFR < 60) is compromised. Returns alternative treatments if safety thresholds are breached. get_patient_details: Fetches clinical metrics (conditions, eGFR, active medication list) for a patient. add_patient: Inserts a new patient record into either the live Supabase database or the local fallback cache. list_interaction_rules: Allows searching the dataset of clinical interaction rules. 2. Database & Schema Initialization (database.tools.ts) setup_medguard_database: Automates table creation and seeds initial patient/interaction rules into Supabase/PostgreSQL using supabase-schema.sql . Supabase Schema: Exposes the database structure as an MCP Resource. 3. Standardized Workflows & Prompts process_patient_workflow: A prompt template guiding the agent to verify patients, safely add new ones, inspect active drugs, and perform the safety evaluation. medguard_q
Who built MedGuard - an ai that assists patients?
MedGuard - an ai that assists patients was built by team INIT MINDS 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.