Fragrance memory, retail intelligence, and AI-ready scent data.
Sniffopotamus
Browse public country showcases first. When you want private memory, start a cabinet, then grow into gift guidance, share cards, retailer tools, MCP access, and structured fragrance data.
Public discovery
Country showcases are open by design.
The public job is discovery: show Australian houses, organise them by style and note, and help people find local makers before asking them to create an account. Sign-in is for private memory, cabinet actions, AI limits, MCP, and paid work surfaces.
Open Country ShowcaseChoose A Path
Three ways into the same fragrance brain.
The same underlying corpus powers different jobs: remembering what you wear, helping fragrance businesses guide customers, and giving builders clean data to work with.
Track the bottles you own, remember what you wear, build wishlists, make gift choices easier, and turn your real scent life into shareable cards.
02For BusinessRetailers, boutiques, and brandsUse the fragrance graph for gift finding, fuzzy search, catalogue cleanup, note imagery, and privacy-safe brand intelligence.
03For BuildersDevelopers, agents, and data teamsBuild with fragrance search, MCP tools, widgets, image assets, and structured data instead of starting your own corpus from zero.
Personal fragrance memory
For the people who wear it, collect it, gift it, and talk about it.
Sniffopotamus starts as a private cabinet and wear diary. Add bottles, log wears, save grails, link with a partner, and let Sniffopotobot help you understand what you actually reach for.
What It Does
- Public country showcases are open before login; the private cabinet starts when you want memory.
- Cabinet tracking for full bottles, samples, decants, backups, and declutters.
- Wear diary with occasion, weather, compliments, sprays, and notes over time.
- Wishlist, grails, partner gift mode, share cards, and yearly Wrapped moments.
- MCP-ready memory so compatible AI tools can read your fragrance context when you allow it.
Do I need to be a serious collector?
No. Start with one bottle. The value grows as you add wears, wishes, samples, and the scents connected to people or moments.
Is my cabinet public?
No. Your cabinet is private by default. Public pages and share cards are intentional surfaces you choose to create.
What does the AI actually use?
It uses your cabinet, wear history, wishlist, partner link, and the fragrance corpus. It should answer from your data, not generic perfume advice.
Commercial fragrance tools
For stores and houses that need fragrance data to sell smarter.
A fragrance business does not need another generic quiz. It needs product matching, cleaner catalogue data, gift guidance, note assets, and a way to understand what real fragrance users are wearing and wanting.
What It Does
- Gift Finder and fuzzy-search widgets for Shopify, online retail, and in-store staff.
- Catalogue cleanup, SKU matching, product feed enrichment, and confidence-tiered corpus onboarding.
- Brand intelligence built from aggregated, anonymised wear, wishlist, and collection signals.
- Note image assets and fragrance passport pages for richer product detail pages.
Does Sniffopotamus sell fragrance directly?
No. The platform is the intelligence layer. Retailers can receive high-intent traffic, but Sniffopotamus does not need to become the checkout.
Can this work for a small store first?
Yes. The first commercial wedge is simple: hosted widgets, catalogue cleanup, Shopify readiness, and pricing that does not require enterprise procurement.
Can a brand keep its data accurate?
Yes. Brand onboarding can load official notes, images, variants, house pages, and evidence tiers so the public corpus is cleaner than community-only data.
API, MCP, and AI infrastructure
For people building fragrance features, agents, and data products.
The consumer app is only one surface. Underneath it is a structured fragrance graph, fuzzy matching, note imagery, MCP tools, and a path toward commercial API access.
What It Does
- Fragrance search, detail, similar, by-note, and fuzzy match endpoints.
- MCP access for cabinet, wear diary, wishlist, discovery, and fragrance oracle tools.
- Hosted widgets for search, gift finding, and future Scent Profile Connect flows.
- Future note image API, visual asset library, and commercial agent licensing.
Is the API separate from the app?
It is a separate commercial surface built from the same corpus. Consumer accounts, merchant tools, and developer access should share the graph without sharing private user data.
Which AI tools fit the MCP path?
Any compatible MCP client can be supported as access matures. The product direction includes Claude, ChatGPT, Cursor, Gemini, and commercial agent contexts.
Can agencies and SaaS builders resell it?
Yes, that is one of the cleanest global routes: agencies can install widgets, enrich catalogues, and build client tools on top of the Sniffopotamus data layer.
Why It Matters
The app is only the first surface.
Sniffopotamus becomes more valuable as the public country corpus gets cleaner, private memory gets richer, and more tools can ask the same fragrance graph better questions.
- Private cabinet first
- Corpus-backed answers
- Retailer-ready widgets
- MCP and API direction
- No marketplace dependency
- Help guides on sniffopotamus.dev
FAQ
A clear answer before the dashboard.
What is Sniffopotamus in one sentence?
Sniffopotamus is a fragrance memory and intelligence layer: personal tracking for users, commercial tooling for fragrance businesses, and structured data access for builders.
Why have a public landing page before the app?
New visitors need to understand the three doors before they see a dashboard. Signed-in users still go straight back to the app experience.
Do I have to pay or sign in to browse Australian houses?
No. Country showcases and the Australian house guide are discovery surfaces. Payment gates belong on private memory, MCP, share-card volume, business dashboards, and builder tools.
Where do detailed setup guides live?
Detailed help, MCP setup, Shopify readiness, API planning, billing, and business guides live on sniffopotamus.dev so the public homepage can stay clean.
How does this stay trustworthy?
The product should separate private user memory from aggregated business intelligence, expose confidence tiers in the corpus, and avoid selling raw user data.
Start with one bottle.
Browse the public showcase first. Build your scent memory when you are ready. The business tools, API access, and agent integrations all make more sense once the fragrance graph is doing real work.