Enterprise AI & Workplace Automation SynergySubmitted July 26, 2026

RetailMind — AI-Powered Retail Location Intelligence

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

About this project

AI-powered retail location intelligence. Enter business type, city, budget & radius — RetailMind analyzes competitors, demographics, and footfall potential across candidate zones via an MCP multi-agent architecture, then ranks them with an explainable 0–100 Opportunity Score. Built with TypeScript, NitroStack, Geoapify & WorldPop.

Enterprise AI & Workplace Automation track

Develop AI agents and automation tools that improve productivity, streamline workflows, and enhance business operations.

Source code

Team Synergy

  • Aryan BhupathiLead

  • Rikhitha Reddy Malikireddy

  • GUNDALA PURAN BHAVANI REDDY

  • Paturu Saichandana

← All Amrita University Coimbatore projects

Frequently asked questions

What does RetailMind — AI-Powered Retail Location Intelligence do?
AI-powered retail location intelligence. Enter business type, city, budget & radius — RetailMind analyzes competitors, demographics, and footfall potential across candidate zones via an MCP multi-agent architecture, then ranks them with an explainable 0–100 Opportunity Score. Built with TypeScript, NitroStack, Geoapify & WorldPop.
Who built RetailMind — AI-Powered Retail Location Intelligence?
RetailMind — AI-Powered Retail Location Intelligence was built by team Synergy at the Amrita University Coimbatore NitroStack × MCP To The Moon hackathon, in the Enterprise AI & Workplace Automation 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.