Build an Internal Dashboard
The opposite of a marketing site: a dense, function-first admin tool for your team or your customers' ops. Material UI for speed, custom shadcn if you must brand it.
A multi-page admin with auth, role-based access, data tables, charts, and CSV export.
Framework + UI
2 repos
Server components keep heavy queries off the client.
The React framework. ~128k stars. App Router is the bet — server components, server actions, edge runtime. 2026 sentiment is mixed: people l…
Faster to assemble dense admin UIs than rebuilding shadcn primitives.
The safe enterprise pick. Massive component library, well-documented, every internal admin tool uses it. Price: your app will look like ever…
Tables + Data
2 reposReactive client store synced from server. The new pattern for dashboards.
New 2026 entry from TanStack — local-first reactive DB for offline-capable apps. Worth watching but ecosystem is still young.…
When you want pure server-state caching without the store layer.
The #1-rated tool in the React 2025 survey. Async state management — fetching, caching, syncing server state. Not a state library exactly bu…
Charts
3 repos
Decent defaults, decent API. The pragmatic React choice.
Composable charting library for React. ~24k stars. Built on D3 but with a much friendlier API. Default choice for dashboards and analytics U…
When you need real interactivity — zooming, brushing, large datasets.
Mature, feature-rich charting library with strong support for complex chart types (sankey, treemap, candlestick). Heavier than Recharts but …
When the chart you need does not exist anywhere else.
The data visualization library. ~108k stars. Steep learning curve but unmatched flexibility. Used under the hood by most React charting libr…
- DB + Auth2 repos
- Forms + Validation2 repos
- Tables (advanced)1 repo
- Layout + drag2 repos
- Auth + RBAC1 repo
- Export + reporting2 repos
- Component documentation1 repo
- Email (digest / alerts)1 repo
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See pricingThe 4-step AI workflow
The AI agents are good at code. They're bad at deciding what stack to use. This bundle does the second part. You bring the agent.
- 1Ideate with ChatGPT or Claude.ai (web)Paste your idea: “I'm building build an internal dashboard. Help me sharpen the product spec — features, edge cases, MVP scope.” Iterate for 10-15 minutes until you have a clear one-page brief.
- 2Pick your coding agentFor this kind of bundle, we recommend Claude Code — Sonnet 4.6/4.7 handles full-stack multi-file reasoning best. See the install guide → Cursor and Codex are also great; pick the one you already pay for.
- 3Feed this bundle to the agentOpen Claude Code / Cursor / Codex in an empty folder, then paste:
I'm building build an internal dashboard. Use this bundle as the source of truth for the stack: https://stackpicks.dev/build/internal-dashboard Brief from my product spec: [paste your brief from step 1] Follow the bundle order strictly: 1. Framework + UI 2. Tables + Data 3. Charts 4. DB + Auth ... Stop and confirm with me after each layer.
- 4Wire one layer at a time, commit between eachDon't let the agent install everything before the first
git commit. One layer = one commit. Catches drift early, easy rollback.
Beyond the bundle
- 1Ship the boring version first. The bundle above is the maximalist list. For an MVP, start with 60% of these and add the rest when real users ask.
- 2Deploy early. Push to Railway / Vercel after layer 02 (auth) — not after layer 09. Production breaks differently than localhost.
- 3Read CLAUDE.md / .cursor/rules in this repo for the project conventions your AI agent should follow.
- 4Iterate on the take. If a repo here doesn't fit your specific use case, tell us — contact — and we'll add a better one within 60 minutes.