Portaljs

PortalJS

<b>The AI-native framework for building data portals.</b>

Describe the portal you want — your agent helps you choose an architecture, scaffolds it, and loads your data.


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Quickstart

Create a portal — one command, nothing to install beyond Node 22+:

npm create portaljs@latest my-portal
cd my-portal
npm run dev      # → http://localhost:3000

You get the three surfaces — Home, a Catalog (/search), and a dataset Showcase (/@<namespace>/<slug>) — over sample data. Plain, editable Next.js, no lock-in. Add your own CSV/JSON to datasets.json and it renders automatically.

Build it with your AI assistant — PortalJS ships Claude Code skills that do the assembly. Install them once (into ~/.claude/commands):

curl -fsSL https://raw.githubusercontent.com/datopian/portaljs/main/scripts/install-portaljs-skills.sh | bash

Then, in a Claude Code session from any directory:

/portaljs-architect    not sure what stack you need? start here
/portaljs-new-portal   "Auckland Council open data portal"
/portaljs-add-dataset  ./data/air-quality.csv

/portaljs-new-portal scaffolds the three surfaces; /portaljs-add-dataset (or /portaljs-add-resource) loads data; /portaljs-connect-ckan points it at a CKAN backend; /portaljs-deploy ships it. (All skills + install →)

Prefer the bare template — plain Next.js, no AI, no lock-in:

npx tiged datopian/portaljs/examples/portaljs-catalog my-portal
cd my-portal && npm install && npm run dev      # → http://localhost:3000

You get Home, a Catalog (/search), and a dataset Showcase (/@<namespace>/<slug>) over sample data. Add your own CSV/JSON to datasets.json and it renders automatically.

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Why PortalJS

Building a data portal has always meant more than a website. You have to decide where the data lives, how it's versioned, how people search it, how it's served, and how it's governed — and then wire a frontend on top. Teams either over-build on a heavy data warehouse they don't need, or under-build on a pile of scripts that doesn't scale.

PortalJS is an open-source, agentic skills framework that helps data teams build, develop, and ship data portals — and the data infrastructure underneath them. It isn't only a frontend. The skills do two jobs:

• Advise — given what you're building, what your data is, and what it's for, they recommend an architecture: storage, compute, catalog, access, hosting, metadata.
• Build — they scaffold that stack as plain, editable Next.js code with no lock-in.

It is opinionated but open: the recommended modern path is git + object storage (Cloudflare R2) + Parquet, queried with DuckDB — an open lakehouse instead of a classic warehouse. For living, incremental tables you can layer on DuckLake, and a traditional datastore (CKAN, a warehouse) stays a first-class option when you need it. You always own plain code.

Built and maintained in the open by Datopian and the PortalJS community.

Architecture at a glance