Open Knowledge Format (OKF): Google's New Markdown Format for AI Agents

A few weeks ago I published a long post on making a website agent-ready. It runs through robots rules, llms.txt, schema, markdown negotiation, MCP cards and more, and almost none of it is officially acknowledged by anyone yet. It is a stack of educated bets. Last month Google turned one of those bets into a published standard, the Open Knowledge Format, and unlike most things Google ships you can write one in a text editor.

It arrived quietly, bolted to a rebrand. Google spent years selling Dataplex as enterprise data plumbing nobody outside a data team ever thought about. It is now Knowledge Catalog, described as an “always-on context engine” for AI agents. The product barely moved. The positioning moved completely, which I wrote about when it shipped. OKF is the portable, open piece of that launch, and it is the piece worth your time.

What OKF actually is

Underneath, OKF is plain. A bundle is a directory of markdown files. Every file carries a short block of YAML up top, the type of thing it is, a title, a description, and it links to its neighbours like any markdown document would. An agent reads it as is, with no scraping and no API in the way.

Here is what a single file looks like, since a whole bundle is just a folder of these.

---
type: Article
title: How to Connect the Ahrefs MCP Server to Manus
description: The official MCP servers, why they did not connect, and the fix.
resource: https://yoursite.com/blog/ahrefs-mcp-manus/
tags: [mcp, ahrefs]
---

# How to Connect the Ahrefs MCP Server to Manus

The body of the post, as clean markdown.

Add an index.md that lists the files so an agent can see what is there before opening everything, and that is the format. There is no registry to join and nothing to install. Google’s spec fits on a single page.

Where OKF fits

The web is quietly growing a second layer, one written for machines instead of browsers, and OKF is its newest floor. Sitemap.xml tells a crawler which URLs exist. llms.txt points an agent at the handful of pages you most want read. EntityMap, a separate spec I shipped here last month, declares which entities you own, you, your company, the topics you want your name stuck to, and how they relate. OKF goes one floor higher again and hands over the content itself, every page as a clean markdown concept, cross-linked into a graph an agent can walk.

They stack rather than compete. llms.txt is a signpost, EntityMap is a who’s who, and OKF is the library itself.

Why it carries Google’s weight

EntityMap is a sharp spec from people I rate, Dixon Jones among them, but it is a community effort. OKF was introduced on the Google Cloud blog and ships inside Knowledge Catalog, a live Google product. Google describes it as formalising the “LLM-wiki” pattern, the markdown-and-frontmatter idea that has been surfacing as Obsidian vaults, AGENTS.md files and llms.txt for the past year. When Google standardises a pattern you have already bet on, that is worth noticing, even at version 0.1.

The GitHub repo says it is “not an official Google product”, which looks like a contradiction next to a Google Cloud blog launch. It is not. Google puts that same disclaimer on most of its open-source repos, its main AI samples repo included. It only means the code is unsupported, not that the format is unofficial. Google wrote the spec and announced it. The boilerplate is just doing its usual lawyerly job.

What it does for AI search

A bundle will not move your rankings or your AI visibility this week. Nothing crawls the web for these bundles yet, the spec is weeks old, and Google built it for data teams sharing tables and metrics, not for blogs. Pointing it at a website is a repurposing. A good one, but a repurposing.

What it does do is make your content effortless to read the day an agent comes looking. The body is clean markdown with the navigation and ads stripped out, every page is tagged with what it is, and the internal links survive as a graph, so an agent sees not just your pages but how they connect. That relationship layer is what a flat scrape throws away. You are not buying a ranking. The win is a site the systems sitting between your writing and your reader can actually understand.

How to make your own bundle

There are 3 ways to turn a site into an OKF bundle.

The first is by hand. Fine for a few pages, miserable for a whole site, since every post becomes a file you format and cross-link yourself.

Exporting from a data catalogue is the second, which is the enterprise route and assumes your content already lives in one. Yours almost certainly does not.

The third is the free tool I built. Paste your URL or your sitemap and it crawls up to 100 pages, converts each one to a clean OKF concept, links them into a graph, and gives you the bundle as a download, without writing code or signing up.

It also draws your site the way an agent sees it, every page a dot and every internal link a line, so the islands with nothing pointing in or out are obvious at a glance. That alone is a free structural audit.

You can find the tool at /okf-generator/. I built it the same time I turned my own site into a bundle, so it is the exact engine running here, just pointed at your pages instead of mine.

Hosting it on your site

A bundle only helps if an agent can find it, so serve the files at yoursite.com/okf/, starting with /okf/index.md. On a static host or Cloudflare that is a drag and drop. On WordPress it is a file upload, a little more fiddly. On closed platforms like Wix or Squarespace you often cannot serve files at a custom path, which is the one real wall. Add a line to your llms.txt pointing at the bundle and you are done.

Whether it is worth your time

So is it a must? No. Skip it and nothing breaks today, and anyone calling a 0.1 draft mandatory is selling you something. It is a nice-to-have. What tips it past the bar is the asymmetry. The cost is a free tool and a drag and drop, and the structural map you get back is a real audit on its own, even if no agent ever opens the bundle.

I have made this bet before, with EntityMap. Protocol-layer work is registration, not advertising. You put it down early, let it compound, and forget it is there. Schema took the best part of a decade to pay off, and I am still glad I shipped it early. This is the same shape of bet, now with Google’s name on it.