An honest comparison — including where MyFitnessPal is the better choice.
If you've used MyFitnessPal, you know the workflow: open the app, tap the search bar, type the food, scroll through the results, pick the closest match, specify the portion size, and tap save. Repeat for every component of the meal. That process works — when you're motivated enough to do it three times a day for the rest of your life.
Salamati works differently. You tap the mic and say what you ate. "Chicken and rice bowl with some broccoli, medium sized." Two seconds later, the entry is logged with protein, carbs, fat, and calorie estimates. Tap to review, optionally edit, done. The same voice-first approach works for workouts, supplements, sleep, and mood check-ins.
This isn't a minor UX difference. The research on habit formation consistently finds that logging apps fail because of friction, not lack of intent. When logging is slow, people subconsciously avoid meals that are hard to log — or stop logging entirely. The average MyFitnessPal user quits within three weeks. The average Skrypt session takes under 12 seconds per entry.
The right question isn't "which app has more features?" It's "which app do you still use in week four?"
| Feature | Salamati | MyFitnessPal |
|---|---|---|
| Primary logging method | Voice / natural language | Barcode scanner + food database search |
| Average time to log a meal | < 12 seconds | 60–120+ seconds |
| Nutrition tracking | AI macro estimation | Database with verified labels |
| Fitness tracking | Voice — any description | Exercise database search |
| Supplement tracking | Stack system + voice logging | Limited / manual |
| Sleep tracking | Voice log with context | Not available |
| Mood tracking | Voice check-ins | Not available |
| Cross-domain insights | Ask Skrypt (AI over your history) | Not available |
| Food database precision | AI estimation (editable) | 8M+ verified food items |
| Restaurant / chain foods | AI estimation | Chain restaurant database |
| Barcode scanning | Not available | Yes |
| Price | Free (early access) | Free tier limited · Premium $19.99/mo |
| Privacy / data sales | Data never sold | Data used for ads (free tier) |
| Platform | Web + PWA (iOS/Android via browser) | iOS + Android native apps |
You want logging to take under 15 seconds — and you've found yourself skipping entries when they feel too slow.
You want to track more than calories. Your sleep affects your workouts. Your supplements affect your energy. Your mood affects what you eat. Skrypt models all of it together.
You hate barcode scanning. Finding the right item in a food database takes cognitive effort that disrupts the flow of eating.
You want your data to stay private. Skrypt does not sell health data or use it for advertising. Voice audio is discarded immediately after transcription.
You're on a budget. Skrypt is free during early access and will maintain a generous free tier when paid features launch.
You need gram-precise macro tracking from verified nutrition labels — especially for packaged foods or restaurant chains where exact counts matter (e.g., competition prep, clinical diet).
You already have years of history in MyFitnessPal and rely on the trend data.
You want barcode scanning for quick packaged food logging.
You rely on the MFP social community and friend tracking features.
You need a native iOS or Android app rather than a PWA.
The data on tracking app retention is sobering. Studies consistently find that most users of food logging apps stop logging within two to four weeks of starting. The reason isn't motivation — people want to track. The reason is that the act of logging intrudes on the experience of eating and living.
The barrier isn't finding a food in the database, exactly. The barrier is that the entire mental model — stop, open app, search, log — requires switching from "living" mode to "data entry" mode. That mode switch has a cost, and people avoid it when life gets busy.
Salamati's design constraint is that logging should never take you out of the moment. You're already narrating your day in your head — "I had a good workout, I'm making eggs" — we just capture that narration. The voice interaction is so fast that you can do it while you're still eating, still stretching, still waking up. That's a fundamentally different habit to build, and it's one that sticks.
The five-domain structure also matters for consistency. On MyFitnessPal, a "bad" day nutritionally feels like a failure to record. On Skrypt, the same day might still have great sleep data, solid supplement adherence, and a mood check-in — so there's always a reason to log, even when nutrition is messy.
This is a fair question and deserves an honest answer. MyFitnessPal's verified food database — built from product nutrition labels, restaurant published data, and USDA records — is more precise for any specific food item that exists in the database. If you scan a specific brand of Greek yogurt, you get that yogurt's exact nutrition label.
Skrypt's AI estimation is trained to understand how people describe food in natural language and to estimate macros for common preparations. For home-cooked meals, common whole foods, and typical restaurant dishes, the estimates are accurate enough for the goal most users have — understanding patterns across weeks, not hitting a specific macro target to the gram.
The practical difference: if you log "chicken breast, broccoli, brown rice," Skrypt will give you a reasonable macro estimate for a typical preparation. If you're preparing for a bodybuilding competition and need to know the macros of a specific 165g portion of a specific brand of chicken breast, MyFitnessPal's database is more precise.
For the other 95% of users — people who want to understand whether they're eating enough protein, whether they're consistently low on sleep, whether their supplement routine is consistent — Skrypt's approach is accurate enough and dramatically faster.
Any estimate in Skrypt can be edited after the fact. So if you know the real macro count for something, you can log it with your actual values.
MyFitnessPal is, at its core, a calorie and macro counter. It does that well. But nutrition doesn't exist in isolation — the way you sleep affects how much you eat the next day. Your supplement routine affects your training quality. Your mood affects your food choices. None of these connections show up in an app that only tracks nutrition.
Skrypt tracks all five domains — nutrition, fitness, supplements, sleep, and mood — with the same voice-first approach. The real value isn't the individual logs: it's what you learn when you can ask "what was my sleep like on days I worked out in the morning?" or "how does my mood track against my protein intake?" over months of real data.
The "Ask Skrypt" feature is a conversational AI that queries your personal health history. You ask it things like "what's my average protein intake this week?" or "was my sleep better when I took magnesium?" and it answers from your actual data. There's no equivalent feature in MyFitnessPal.
