Open Innovation ctrl+alt+defeatSubmitted July 18, 2026

Harmoni-Q — An AI DJ Advisor MCP that analyzes audio to build the perfect setlist

An MCP app on the Model Context Protocol built by ctrl+alt+defeat at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon and deployed on NitroStack.

About this project

Harmoni-Q is an intelligent DJ assistant built as an MCP server that brings advanced audio analysis directly into any AI chat environment (ChatGPT, Claude, NitroChat). It solves a core problem for DJs and music enthusiasts: knowing if two tracks will mix well together before ever touching the decks. Key Features: 1. Deep Audio Analysis: Uses WebAssembly (WASM) based signal processing to extract exact BPM, beat density, and metadata from raw audio files or public URLs. 2. Mix Compatibility Scoring: Compares tracks based on tempo, energy, and rhythm structure to generate a "mixability" score, warning users about potential trainwrecks. 3. Intelligent Set Ordering: Uses graph traversal algorithms and Google's Gemini AI to take a list of disorganized tracks and arrange them into a perfectly flowing setlist that builds energy over time, complete with a narrative explanation of how to execute each transition. What makes it special is its architecture. By building this as a NitroStack MCP server rather than a standalone app, Harmoni-Q can be instantly plugged into ChatGPT. Users can simply chat naturally with their AI assistant, say "Analyze this track", and Harmoni-Q processes the complex audio physics in the background and visualizes the results with beautiful, interactive React widgets right in the chat.

Open Innovation track

Solve any real-world problem with AI, regardless of industry or domain.

Team ctrl+alt+defeat

  • Praveen MutyalaLead

  • M SRIRAG SARMA

  • Maddali Tej Vardhan

  • Chakradhar Sriram Karthik D

Frequently asked questions

What does Harmoni-Q — An AI DJ Advisor MCP that analyzes audio to build the perfect setlist do?
Harmoni-Q is an intelligent DJ assistant built as an MCP server that brings advanced audio analysis directly into any AI chat environment (ChatGPT, Claude, NitroChat). It solves a core problem for DJs and music enthusiasts: knowing if two tracks will mix well together before ever touching the decks. Key Features: 1. Deep Audio Analysis: Uses WebAssembly (WASM) based signal processing to extract exact BPM, beat density, and metadata from raw audio files or public URLs. 2. Mix Compatibility Scoring: Compares tracks based on tempo, energy, and rhythm structure to generate a "mixability" score, warning users about potential trainwrecks. 3. Intelligent Set Ordering: Uses graph traversal algorithms and Google's Gemini AI to take a list of disorganized tracks and arrange them into a perfectly flowing setlist that builds energy over time, complete with a narrative explanation of how to execute each transition. What makes it special is its architecture. By building this as a NitroStack MCP server rather than a standalone app, Harmoni-Q can be instantly plugged into ChatGPT. Users can simply chat naturally with their AI assistant, say "Analyze this track", and Harmoni-Q processes the complex audio physics in the background and visualizes the results with beautiful, interactive React widgets right in the chat.
Who built Harmoni-Q — An AI DJ Advisor MCP that analyzes audio to build the perfect setlist?
Harmoni-Q — An AI DJ Advisor MCP that analyzes audio to build the perfect setlist was built by team ctrl+alt+defeat at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon, in the Open Innovation 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.