Most of the web treats AI agents as intruders. We think the next decade of visitors will be people and their agents, so we built this site for both. Everything below is live on this domain today.
Every public data page carries a rel="alternate" link to its API equivalent: the catalog to /v1/catalog, a source page to its datasets endpoint, a series page to its observations. The { } control in the header opens the twin in one click.
No agent should have to parse our HTML. Request any data page with Accept: application/json (or ?format=json) and it redirects straight to the structured answer.
/llms.txt is the site in one screen: what this is, where the docs are, where the API lives. /llms-full.txt is the complete documentation as a single markdown file, generated from the same source as the human docs.
Every series page publishes schema.org Dataset markup with its license, temporal coverage, and CSV and JSON distributions. The catalog publishes DataCatalog.
The store speaks Model Context Protocol natively. Point any MCP client at https://starwell.dev/api/starwell/mcp and verified statistics become tools: search, observations, computed answers, deep analysis, monitors. An agent reads the same store this website reads.
Agents get the same rate limits and the same free keys as people. Every value cited on a page carries that citation in the API response too.
The machine surfaces expose what the human pages expose. Accounts, keys, and usage stay behind authentication and out of every machine manifest.
{ } on the catalog or any series page.curl -H "Accept: application/json" https://starwell.dev/catalogNone of this needs a framework:
rel="alternate" links from every content page to its structured equivalent.Accept: application/json on those pages with a redirect to the data./llms.txt, and /llms-full.txt if you have real documentation.If you adopt the pattern, or think it should say something it does not, write to hello@starwell.dev.