Building a Modern Web MVP: From Zero to Production in Record Time

Shipping a production-ready MVP quickly while maintaining code quality is the holy grail of modern web development. In this article, I’ll walk through my approach to building full-stack applications that are type-safe, secure, and deployment-ready from day one—leveraging both cutting-edge frameworks and AI-assisted development.

The Modern MVP Stack

After iterating on multiple projects, I’ve converged on a stack that maximizes developer velocity without sacrificing production readiness:

This combination eliminates entire categories of decisions and boilerplate, letting you focus on business logic.

AI-Assisted Development with Claude Code

One of the most significant productivity multipliers in my workflow is Claude Code—an AI coding assistant that understands full project context and can execute tasks autonomously.

MCP Servers: The Game Changer

What sets this approach apart is the integration of Model Context Protocol (MCP) servers. These allow the AI to interact directly with external services:

• Supabase MCP: Query databases, apply migrations, manage schemas directly from the conversation
• Stripe MCP: Search customers, list products, debug payment flows without switching context
• Vercel MCP: Deploy, check logs, manage environment variables

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Developer: "Create a purchases table with RLS policies for user access"

Claude Code: *Analyzes existing schema*
            *Generates migration SQL*
            *Applies via Supabase MCP*
            *Verifies with security advisor*

This tight integration means less context-switching, fewer copy-paste errors, and faster iteration cycles.

When AI Shines (and When It Doesn’t)

AI-assisted development excels at:

• Boilerplate generation: CRUD operations, API routes, type definitions
• Integration code: Connecting services (Stripe webhooks, Supabase auth)
• Debugging: Analyzing logs, tracing issues across the stack
• Documentation: Generating types, API docs, README files

Human judgment remains critical for:

• Architecture decisions: Choosing the right abstractions
• Business logic: Understanding user needs
• Security review: Validating AI-generated code
• UX decisions: What the product should actually do

Project Architecture

A clean, scalable structure from the start prevents technical debt:

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src/
├── app/                    # Next.js App Router pages
│   ├── api/                # API routes (tRPC, webhooks)
│   ├── (auth)/             # Auth-related pages
│   └── admin/              # Protected admin routes
├── server/
│   ├── trpc.ts             # tRPC initialization + context
│   └── routers/            # Domain-specific API procedures
├── lib/
│   ├── supabase/           # Client instances (browser, server, admin)
│   └── stripe.ts           # Stripe client configuration
├── components/             # Reusable UI components
└── hooks/                  # Custom React hooks

Key principles:

• Colocation: Keep related code together
• Clear boundaries: Server code never leaks to client bundles
• Type safety: Shared types flow from database to UI

End-to-End Type Safety with tRPC

The single biggest productivity boost comes from eliminating the API boundary as a source of bugs:

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// server/routers/products.ts
export const productsRouter = router({
  list: publicProcedure
    .input(z.object({
      category: z.string().optional(),
      minPrice: z.number().optional(),
      maxPrice: z.number().optional(),
    }))
    .query(async ({ input }) => {
      // Input is validated and typed automatically
      const products = await db.query(...)
      return products // Return type is inferred
    }),
})

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// Client component - full autocomplete, zero runtime surprises
const { data } = trpc.products.list.useQuery({ category: 'electronics' })
// data.map(...) - TypeScript knows the exact shape

No OpenAPI specs to maintain. No code generation step. Change the server, and TypeScript immediately flags client-side issues.

Database Security with Row Level Security

Supabase’s RLS lets you define security rules at the database level:

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-- Users can only read their own purchases
CREATE POLICY "Users read own purchases" ON purchases
  FOR SELECT USING (user_id = auth.uid());

-- Only admins can modify products
CREATE POLICY "Admins manage products" ON products
  FOR ALL USING (
    EXISTS (
      SELECT 1 FROM profiles
      WHERE id = auth.uid() AND is_admin = true
    )
  );

Why this matters:

• Security bugs in application code can’t bypass database rules
• Policies are auditable and version-controlled
• Defense in depth: multiple layers of protection

Payment Integration with Stripe

For MVPs, Stripe Checkout is the fastest path to accepting payments:

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// Create checkout session with metadata for webhook processing
const session = await stripe.checkout.sessions.create({
  mode: 'payment',
  line_items: [{
    price_data: {
      currency: 'usd',
      product_data: { name: product.name },
      unit_amount: product.price, // in cents
    },
    quantity: 1,
  }],
  metadata: {
    user_id: ctx.user.id,
    product_id: input.productId,
  },
  success_url: `${APP_URL}/success?session_id={CHECKOUT_SESSION_ID}`,
  cancel_url: `${APP_URL}/cancel`,
})

The webhook handler processes successful payments:

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// api/webhooks/stripe/route.ts
if (event.type === 'checkout.session.completed') {
  const session = event.data.object

  // Idempotency check
  const existing = await db.getPurchaseBySessionId(session.id)
  if (existing) return { received: true }

  // Record purchase using metadata
  await db.createPurchase({
    userId: session.metadata.user_id,
    productId: session.metadata.product_id,
    stripeSessionId: session.id,
  })
}

Deployment Pipeline

With Vercel, deployment is essentially automatic:

1. Push to main → Production deploy
2. Push to branch → Preview URL generated
3. Open PR → Preview URL in PR comments

Environment variables are managed per-environment (development, preview, production), and rollbacks are one click away.

For additional validation, a simple CI workflow ensures code quality:

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name: CI
on: [push, pull_request]
jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: npm ci
      - run: npm run lint
      - run: npm run build

Development Workflow Summary

1. Define data model → Supabase migrations with RLS
2. Build API → tRPC procedures with Zod validation
3. Create UI → shadcn/ui components with Tailwind
4. Add payments → Stripe Checkout + webhooks
5. Deploy → Push to main, Vercel handles the rest

With AI assistance handling boilerplate and integration code, the focus stays on what matters: building features users actually need.

Key Takeaways

• Type safety eliminates bugs: tRPC + TypeScript catches errors before runtime
• Managed services reduce ops burden: Supabase and Vercel handle infrastructure
• AI accelerates, humans validate: Use Claude Code for speed, review for quality
• MCP servers bridge the gap: Direct service integration from your development environment
• Ship early, iterate fast: The best architecture is one that lets you learn from real users

The modern web development landscape offers unprecedented leverage. By combining the right tools with AI-assisted development, shipping a production-quality MVP is faster than ever—without cutting corners on security or code quality.

Questions about this stack or approach? Connect with me on LinkedIn .