At Asper Brothers, we work with founders to turn product ideas into working MVPs, so the stack below reflects the technologies we actually use in real client projects — not a theoretical list of popular tools.
| Layer | Our typical choice |
|---|---|
| Web frontend | React |
| Mobile | React Native |
| Web UI | DaisyUI + our internal boilerplate |
| Mobile UI | React Native Paper + our internal boilerplate |
| Product design | Figma |
| Backend & database | Supabase |
| Web deployment | Vercel |
| Mobile builds & deployment | Expo EAS |
| Source control | GitHub |
| CI/CD | GitHub Actions |
| Transactional email | Resend |
| Payments | Stripe |
| Mobile backend alternative | Firebase |
| AI | OpenAI API / Anthropic / Mistral |
| Maps | Mapbox / Google Maps |
| Other functionality | Project-specific third-party APIs |
That doesn’t mean every MVP should use every tool above.
It means we have a default, proven path for common MVP requirements and deviate from it when the product, client infrastructure, security requirements, regulations, or a specific integration gives us a reason to.
That distinction is important.
A good MVP tech stack isn’t the stack with the most technologies. It’s the smallest set of proven technologies that lets you ship the product you need to validate.
An MVP tech stack is the combination of frameworks, infrastructure, development tools, and third-party services used to build and operate a Minimum Viable Product.
For a typical web or mobile product, it may cover:
The mistake is assuming you need to build each of these layers yourself.
You usually don’t.
One of the biggest differences between building an MVP today and building one a decade ago is how much reliable infrastructure is available as a managed service.
Instead of spending MVP budget building authentication, payment infrastructure, transactional email, deployment tooling, or an entire backend platform from scratch, we can use mature services and focus engineering time on the functionality that actually differentiates the product.
That’s the philosophy behind our MVP stack.
The best MVP tech stack isn’t the one with the most impressive architecture. It’s the one that helps you launch quickly, learn from real users, and keep building without having to start over once the product gains traction. Co-Founder, Asper Brothers Build Your MVP
If we had to start a fairly standard web MVP tomorrow, our first option would typically be:
React + DaisyUI + Supabase + Vercel + GitHub Actions + Resend, with Stripe added when the product needs payments.
For a mobile MVP, the default changes to:
React Native + React Native Paper + Supabase + Expo EAS + GitHub Actions, with Firebase considered when it makes more sense for the application’s mobile requirements.
For an AI-enabled MVP, we add the model provider that fits the use case and constraints:
OpenAI API, Anthropic, or Mistral.
This is a starting point rather than a rigid rule.
Here’s why we use each part.
For web MVPs, React is our main frontend technology.
But simply saying “we use React” doesn’t explain much about development speed.
A significant part of MVP velocity comes from not starting every project from an empty repository.
We maintain our own web boilerplate built around React and DaisyUI. It gives the development team a reusable technical and UI foundation instead of rebuilding the same basic application structure for every client.
The product itself does not look like a template.
Each interface is designed for the particular project in Figma and the reusable foundation is styled and adapted to match that design.
This gives us a useful combination:
standardized engineering underneath, custom product experience on top.
For an MVP, this matters because there is little value in repeatedly solving problems the team has already solved.
Reusable foundations let developers spend more time on the workflows, integrations, and functionality that make the client’s product different.
React gives us:
The last point is important.
An MVP stack should optimize for speed, but speed shouldn’t automatically mean “temporary code that we’ll throw away in six months.”
We prefer technologies that work well during validation but can continue supporting the product afterward.
When the product needs native mobile applications, our default is usually React Native.
Instead of developing completely separate iOS and Android applications, React Native allows us to share a significant part of the development effort between platforms.
For an MVP, that can make a major difference.
The goal is usually to test whether users want the mobile experience — not to maintain two independent engineering teams before that assumption has even been validated.
As with our web projects, we don’t begin from zero.
We have an internal React Native boilerplate using React Native Paper as the UI foundation. The interface is then customized according to the product’s Figma designs.
A typical mobile MVP stack therefore looks like:
React Native → React Native Paper → Supabase → Expo EAS
with project-specific integrations added where required.
For many MVPs, Supabase is our default backend platform.
This is one of the areas where our actual stack differs from the traditional approach of automatically creating a custom backend application and infrastructure for every new product.
Supabase can provide several things an MVP commonly needs from one platform, including a PostgreSQL database, authentication, storage, APIs, and backend functionality.
The important benefit isn’t simply that Supabase is convenient.
It’s that it can eliminate a significant amount of undifferentiated backend work.
If we’re building a marketplace, for example, the valuable engineering problems may involve matching users, building the transaction workflow, implementing a specific business process, or integrating an external service.
Building basic authentication infrastructure from scratch does not validate any of those assumptions.
Using Supabase allows more of the MVP budget to go toward the parts of the application that actually need to be custom.
For web MVPs, we commonly deploy with Vercel.
Again, the reason comes back to reducing infrastructure work that does not contribute directly to product validation.
At MVP stage, we want deployments to be:
The team should be able to ship a change, test it, and put it in front of users without turning every release into an infrastructure project.
As the product grows, infrastructure requirements may change. That’s fine.
The objective at MVP stage is not to predict every infrastructure requirement the company will have three years from now.
It’s to have a reliable deployment setup for the product it needs today.
For React Native projects, we commonly use Expo EAS for application builds and deployment workflows.
Mobile releases involve additional complexity compared with deploying a web application: iOS and Android builds, signing, app-store requirements, environment configuration, and distribution all need to be managed.
Expo EAS removes part of that operational burden.
That matters particularly for an MVP team because infrastructure and release engineering compete for the same limited development resources as product features.
We’d rather use those resources to improve the product.
Our code lives in GitHub, and we use GitHub Actions for CI/CD automation.
CI/CD isn’t something we postpone until a startup becomes “big enough.”
An MVP is likely to change frequently.
After the first users start testing it, new releases may contain bug fixes, onboarding improvements, analytics changes, experiments, and features based directly on user feedback.
Automating the build, testing, and deployment workflow reduces the friction associated with those iterations.
A good MVP stack isn’t only about getting to version 1 quickly.
It should also make versions 1.1, 1.2, and 1.3 easy to ship.
When an MVP needs transactional emails, we commonly use Resend.
That can include things such as:
Email is a good example of functionality that most startups shouldn’t build infrastructure for themselves.
The application needs reliable email delivery. It usually doesn’t need a custom email delivery platform.
That’s exactly the kind of problem where a specialized third-party service makes sense.
For products that need payments or subscriptions, our standard choice is typically Stripe.
Payment infrastructure is another area where reinventing the wheel is particularly difficult to justify at MVP stage.
Depending on the product, Stripe can support requirements such as:
There can, of course, be projects where another payment provider is required because of geography, business model, existing client infrastructure, or specific commercial requirements.
But Stripe is our usual starting point.
Supabase isn’t a universal answer.
For some mobile applications, we also use Firebase.
This illustrates an important rule behind our approach to MVP technology:
defaults are useful; dogma isn’t.
Having a preferred stack speeds up technical decisions and development. But forcing every application into exactly the same architecture defeats the purpose.
If a product’s requirements make Firebase a better fit, we’ll use Firebase.
The same principle applies to other parts of the stack.
AI features are increasingly common in MVP specifications, but we don’t automatically select the same model provider for every project.
Depending on the use case, we work with:
The choice depends on what the product needs.
That can include model capabilities, cost, latency, integration requirements, client preferences, data processing requirements, and legal or regulatory constraints.
This becomes particularly important when working on regulated applications in Europe.
In some projects, requirements around where data is hosted or processed influence which AI provider and deployment setup can be used.
For applications that require hosting and processing with a European partner, Mistral can become part of the architecture.
This is a useful example of why there is no universal “best AI API for an MVP.”
For an experimental consumer product, model quality and speed of implementation may dominate the decision.
For a regulated European product, data processing and hosting requirements may eliminate options before model benchmarks even enter the discussion.
The technology decision has to follow the product’s constraints.
For products with location-based functionality, we typically work with Mapbox or Google Maps.
The right option depends on what the application actually needs.
A simple location picker, for example, is a different problem from a product where maps are central to the user experience.
Before choosing a mapping provider, we look at requirements such as:
This is another area where choosing the provider before understanding the product requirements is backwards.
The tools above cover our most common foundation.
But real products rarely fit neatly into ten technologies.
Depending on the project, an MVP may need integrations for:
Our default question is:
Does this functionality differentiate the product?
If the answer is no and a reliable third-party service already solves the problem, integrating an API can be much smarter than building the functionality ourselves.
An MVP should contain custom engineering where custom engineering creates product value.
Everything else is a candidate for a proven service.
Let’s make this concrete.
Imagine we’re building a B2B SaaS product with:
A likely starting architecture would be:
Frontend: React
UI foundation: our DaisyUI-based boilerplate, customized from Figma
Backend/database/auth: Supabase
Hosting: Vercel
Repository: GitHub
CI/CD: GitHub Actions
Email: Resend
Payments: Stripe
AI: OpenAI API or Anthropic, depending on the feature
If European data processing constraints affected the AI layer, we might instead evaluate Mistral and an appropriate European hosting/processing setup.
Notice what’s missing:
We aren’t automatically adding Kubernetes, multiple microservices, custom authentication infrastructure, self-hosted email infrastructure, or five different databases.
Not because those technologies are bad.
Because we don’t have a demonstrated reason to add that complexity yet.
Now consider a consumer mobile product requiring:
Our starting point could look like:
Mobile: React Native
UI foundation: React Native Paper + our internal boilerplate
Design: Figma
Backend: Supabase or Firebase, depending on requirements
Build/deployment: Expo EAS
Repository: GitHub
CI/CD: GitHub Actions
Payments: Stripe, where applicable
Maps: Mapbox or Google Maps
Again, the exact stack follows the product.
But starting with a proven default means the team doesn’t have to debate every technology choice from scratch.
There’s an underrated benefit to using similar technologies across multiple MVP projects: the team gets faster at the stack.
Developers know the deployment workflow.
They know the common edge cases.
They know how authentication should be structured.
They know how to connect payments and transactional email.
They have reusable components and project foundations.
They know which shortcuts are safe and which shortcuts create problems later.
That accumulated experience is difficult to see in a list of technologies, but it is one of the biggest advantages of an established MVP stack.
Two agencies might both say they use React.
If one is assembling the architecture for the first time and the other has reusable foundations and established development patterns around it, the actual development process can be very different.
We change the default stack when there is a concrete reason to.
Typical reasons include:
Healthcare, fintech, public-sector, or other regulated products may introduce requirements around hosting, processing, auditability, security, or data residency.
If an organization already operates within a particular cloud environment or technology ecosystem, introducing a completely separate stack may create more problems than it solves.
Products involving intensive computation, specialized real-time workloads, video processing, advanced 3D, or other demanding workloads may need additional technologies.
Sometimes a critical third-party system determines part of the architecture.
Some mobile products benefit from Firebase or require deeper native functionality.
Model performance isn’t the only consideration. Data residency, processing agreements, privacy requirements, and the client’s AI policy can all influence the architecture.
In other words:
Start with defaults. Deviate because of requirements, not because another technology looks interesting.
If you’re choosing a stack for your own product, we’d evaluate it against six questions.
Familiar technology almost always beats theoretically perfect technology during MVP development.
Don’t choose infrastructure for features that aren’t on the roadmap.
Fast development is useful. A forced rewrite immediately after validation isn’t.
Payments, email, authentication, storage, maps, and AI models are obvious areas to investigate before building from scratch.
These should be identified early because they can fundamentally change architecture decisions.
An obscure technology may work technically while creating problems with recruitment, handover, and long-term development.
There is no single stack for every MVP.
But for many web and mobile products, we believe a strong default is:
React or React Native for the application, Supabase for backend and data, Vercel or Expo EAS for deployment, GitHub Actions for CI/CD, Resend for email, Stripe for payments, and proven third-party APIs for functionality that doesn’t need to be built from scratch.
Add OpenAI, Anthropic, or Mistral when the product requires AI, with the provider selected according to functionality, cost, client requirements, and regulatory constraints.
Add Mapbox or Google Maps when location is part of the product.
Use Firebase where it is a better fit for the mobile architecture.
And most importantly, don’t add technology unless you can explain what problem it solves.
The best MVP tech stack isn’t the one that demonstrates how much your engineering team knows.
It’s the one that lets your engineering team spend the largest possible share of its time building what your users actually care about.
An MVP tech stack is the combination of frameworks, databases, infrastructure, development tools, and third-party services used to build and run a Minimum Viable Product. It typically covers the frontend, backend, database, authentication, hosting, deployment, and integrations such as payments, email, AI, or maps.
For many web MVPs, a practical stack is React with Supabase, Vercel, GitHub Actions, Resend, and Stripe where payments are required. For mobile products, React Native with Supabase or Firebase and Expo EAS is a strong starting point. The final choice should depend on the product’s requirements, team experience, and regulatory constraints.
Yes. We use React as our primary frontend technology for web MVPs because of its mature ecosystem, component-based architecture, developer availability, and ability to support a product beyond its initial MVP stage.
For many products, yes. React Native makes it possible to develop iOS and Android applications with a largely shared technology stack, which can reduce development effort and make it well suited to early product validation.
Supabase is our default backend platform for many MVP projects because it combines a PostgreSQL database with services commonly needed by new applications, reducing the amount of backend infrastructure that needs to be built and operated separately.
We generally start with Supabase but use Firebase for some mobile applications. The decision should be based on the application’s requirements rather than treating either platform as universally better.
There is no single best AI provider. We work with OpenAI API, Anthropic, and Mistral depending on model requirements, cost, client preferences, and legal or data-processing constraints. For regulated European applications, requirements around European hosting and processing can materially influence the choice.
Usually, there should be a specific product or technical requirement before introducing microservices into an MVP. Additional services increase deployment, monitoring, testing, and development complexity. For most early products, keeping the architecture simple makes iteration easier.
An MVP should be able to support validation and reasonable early growth without requiring an immediate rewrite. It does not need infrastructure designed for millions of users before demand exists. Optimize for a clear path to scaling rather than maximum scale on day one.
Usually, yes, when the functionality isn’t the product’s core differentiator. Payments, transactional email, maps, AI models, authentication, and other commodity capabilities can often be integrated faster and more reliably than building them from scratch.
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