Most "AI agent" announcements are a demo and a promise. This one is a little different, because it is eleven competitors agreeing on plumbing. On 17 June 2026 a group that includes Google, Microsoft, GitHub, Hugging Face, Cisco, Databricks, GoDaddy, NVIDIA, Salesforce, ServiceNow and Snowflake published a draft open specification called Agentic Resource Discovery, or ARD. It is licensed under Apache 2.0 and builds on the AI Catalog data model maintained by the Linux Foundation. When that many rivals back the same draft, it is usually worth understanding what they are trying to fix, even if you do not need to touch it yet.

The problem ARD is trying to solve

Right now, an AI agent has to be wired up to every tool, MCP server or API it uses ahead of time. Someone configures the connection, the agent learns it, and that is the limit of what it can reach. That works while the list is short. It falls apart as more companies publish capabilities an agent might want to use, because nobody can pre-connect an agent to a web's worth of tools it has never heard of.

ARD moves discovery from a setup step to a runtime search. Instead of being told in advance, an agent can go and find the right tool, skill, API or other agent at the moment it needs one, and verify it before using it. Think of it as the difference between a phone with numbers you saved by hand and a phone that can look anyone up.

How it works, in two pieces

The design is deliberately boring, which is a compliment when it comes to infrastructure. There are two parts:

  • Catalogs. An organisation publishes an ai-catalog.json file at a well-known path on its domain, listing the tools, MCP servers, agents or APIs it makes available. If that pattern feels familiar, it should: it is the same well-known-file idea behind robots.txt and sitemap.xml, pointed at a new audience.
  • Registries. Services crawl those catalogs, index them, and answer an agent's discovery request in plain language, so an agent can ask for what it needs rather than know the exact address in advance.

Trust comes from domain ownership verification, with optional cryptographic metadata for production use. In other words, the thing that proves a capability is really yours is the same thing that proves a website is really yours: control of the domain.

It is not just a paper

The reason to take a v0.9 draft seriously is that backers shipped against it the same day. GitHub launched an agent finder for Copilot. Hugging Face released a Discover Tool for searching skills and MCP servers. Cisco wired it into its AGNTCY Agent Directory. Google's native ARD support is slated for its Gemini Enterprise Agent Platform in "the coming months" rather than today, so the marquee integration is still ahead of us, but the direction is set and the early tooling is real.

The web learned how agents read pages. ARD is the web learning how agents find each other.

The honest part: who this is actually for

Here is where a lot of coverage will overreach, so let us be straight. ARD is aimed at publishers of callable capabilities, the companies that expose tools, agents, MCP servers and APIs. If you run a brochure site, an e-commerce store or a content business, you do not have an ai-catalog.json to publish today, and nothing about this draft changes that overnight. This is not the next thing you must bolt onto your homepage, and anyone telling you to "add ARD" to a marketing site this week is selling urgency.

What it does tell you is where the agentic web is heading, and the pattern underneath it is one we have been making the same point about for a year. The entire spec rests on machine-readable resources, declared at predictable locations, verified by domain ownership. That is the same muscle that decides whether an AI agent can read your products, traverse your checkout and trust who you are. ARD is that principle, extended from "can an agent use your page" to "can an agent find your service at all".

What to take from it, depending on who you are

  • If you publish APIs, tools or agents: read the draft now. Discoverability is about to become a competitive surface of its own, and being in the registries early is the cheap moment to do it. Watch how Google's Gemini Enterprise platform consumes ARD when it lands, because that will shape how everyone else implements.
  • If you run a content or commerce site: nothing to publish yet, but treat this as confirmation of the trajectory. Clean structured data, predictable URLs, content in the HTML and not blocking legitimate agents are the foundations that pay off whichever standard wins.
  • Everyone: standards at the draft stage move and merge. ARD sits alongside MCP, the agent-payment protocols and a growing pile of acronyms. Track the direction, not any single name, and do not re-architect around a v0.9 spec.

Where we come in

Our Agentic AI Readiness Audit tests whether your site, data and flows are machine-navigable today, the same readiness ARD assumes underneath it, and runs real agent journeys against your key pages to show exactly where one gets blocked or stalls. We will tell you plainly what is worth doing now and what is still a slide in someone's deck. That distinction is the whole point of an independent audit: you get the trajectory and the to-do list, without the urgency tax.