Health, home and travel decision
MyFitnessPal Premium
A competent developer can build a useful calorie-tracking replacement that covers the core loop (logging, barcode, basic photo recognition) in about a week and modest monthly operating cost, but reproducing MyFitnessPal's massive food database, device integrations, and scale is impractical without significant data and engineering resources.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Allow a user to create an account, search or add a food item, log meals (text / barcode / photo), compute calories/macros and daily totals, and view simple progress toward BMR/weight goals.
What it still won’t have
- The company's proprietary ~18–20M food database
- Large device/app integrations catalogue (40+ apps & devices)
- Scale, polish, moderation and 280M-user network effects
- Premium-only advanced features and long-term ML improvements
What remains hard
- Proprietary data
one of the world's largest food databases — including fresh foods, packaged goods, restaurant items, and even foods and recipes you save yourself.
- Infrastructure at scale
Join over 280 million people on their journey to eat better, building lasting habits, and reach their goals.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 9 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal cross-platform nutrition tracker (React Native front end, Node.js + Express backend, Postgres DB, Docker). In scope: user auth, profile and goals, daily food diary, food search seeded from OpenFoodFacts, barcode lookup via ZXing and mapping to DB, meal photo recognition using Google Cloud Vision (or similar) to propose foods and quantities, BMR/TDEE and calorie totals, and a web admin to review user-added foods. Out of scope: replicating a 18–20M proprietary food database, certified device integrations, or a large-scale analytics pipeline. Include error handling for failed image/API calls, input validation, and unit/integration tests for API endpoints. Provide docker-compose for local dev and deployment-ready Dockerfiles.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 2 cited sources+1
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-6
- Evidence score56
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
- official productMyFitnessPal official product page
- open sourcesimonoppowa/OpenNutriTracker
Integrity checks
What held up, and what did not.
