A backend engine and logging platform for general health, nutrition, and metabolic tracking (weight, calories, macros) with a Telegram bot interface

USDA FDC API for high-fidelity data ingestion and Supabase for temporal storage, utilizing GitHub Actions to orchestrate bi-weekly variance analysis and automated garbage collection.

iOS app with optimized meal recommendations to help users meet dietary goals before eating

Python MCP server for USDA nutrition data with meal planning system prompts. Get accurate macros, calories, and ingredients for any food item directly in Claude Desktop. Includes automated meal planner for diet-specific recipes.

AI-powered recipe generator that creates personalized healthy meals from your available ingredients with complete nutritional analysis. Built with Streamlit, Groq AI, and USDA data.

AI-powered web app to detect foods from images using AWS Rekognition and estimate calories via the USDA API. Built with HTML, CSS, and JS — fully client-side with no backend.

Upload a food photo, get the calories. AI-powered tracker with BMI calculator, meal-wise logging & personalized daily goals. PHP + Python + MySQL.

Pip's Kitchen Garden — A kid-friendly iOS game where children grow veggies, cook recipes through mini-games, and learn nutrition science with Pip the Hedgehog. Built with SwiftUI, SwiftData, CloudKit, WeatherKit, USDA FoodData Central API, and on-device AI.

An Android app that lets you quickly search and view the nutritional values of any food.

A personal AI health companion — grounded in your own data, and honest about what it doesn't know.

Full-stack nutrition tracking system built with Django, integrating USDA FoodData API for calorie tracking

iOS nutrition tracker: search the USDA food database, log meals, track macros, save favorites, and set daily goals.

An AI-powered hybrid meal recommendation engine designed to provide safe, personalized, and gluten-aware recipes. This system combines deterministic rule-based auditing with dynamic API verification and generative AI analysis to ensure celiac-safe meal planning.

AI-powered Nutrition Analyzer built with Flask, USDA FoodData Central API, SQLite, HTML, CSS, JavaScript, and Chart.js.

High-performance, production-ready FastAPI backend for Caliper running on Python 3.13. Implements strict Pydantic v2 data validation, secure Supabase JWT auth verification layers, and a dual-strategy food search engine combining Open Food Facts and the USDA database.

A Hermes skill for tracking meals, sleep, runs, workouts, injuries, and substances via natural language. USDA-backed nutrition estimates. Data in Google Sheets."

A multi-threaded, non-blocking server built with Java NIO. Implements a scalable event-loop architecture to manage concurrent connections, offloading API requests (USDA FoodData REST API) to a dynamic worker pool.