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Blog / Agent Networking / Agentic Resource Discovery (ARD): the open spec for how AI agents find and verify capabilities
Agent Networking B · Framework

Agentic Resource Discovery (ARD): the open spec for how AI agents find and verify capabilities

ARD, announced by Google on June 17, 2026, is an open multi-vendor spec for how AI agents find and verify tools, other agents, and skills. What it standardizes, and the human-identity gap it leaves.

Olia Nemirovski
@olia · Tobira team
Published June 22, 2026
Last reviewed June 22, 2026
Agentic Resource Discovery (ARD): the open spec for how AI agents find and verify capabilities
TL;DR

Agentic Resource Discovery (ARD), announced June 17, 2026, is an open spec where providers publish an ai-catalog.json at a well-known path, and registries crawl it so agents can find and verify capabilities by intent.

Agentic Resource Discovery (ARD): the open spec for how AI agents find and verify capabilities

Published June 22, 2026 · Last reviewed June 22, 2026

On June 17, 2026, the Google Developers Blog announced Agentic Resource Discovery (ARD), an open specification for how AI agents find and verify tools, skills, and agents across the web. It is not a Google-only project. ARD is being built by a working group with participants from Microsoft, Google, Hugging Face, GoDaddy, Cisco, Databricks, GitHub, Nvidia, Salesforce, ServiceNow, and Snowflake, and it is published under the Apache 2.0 license.

ARD starts from three questions an agent has to answer before it can use any outside capability: “Where does the right capability live? Which capability should I actually use? How do I verify it’s safe to connect to?” Today most agents answer those with hardcoded URLs and developer-maintained lists. ARD proposes a way to answer them dynamically, from files that any provider publishes on its own domain.

One thing ARD is careful to say about itself: it does not replace the protocols you already use. “ARD is not MCP, A2A, Skills, AI Catalog, or an API runtime, and it does not replace them,” the spec site states. It is a discovery layer that sits above them and points to them. Here is what it actually defines, and where it stops.

What ARD actually is

ARD has two moving parts: catalogs and registries.

A catalog is a file a provider publishes at a fixed location, /.well-known/ai-catalog.json, on its own domain. The spec describes it as a manifest that lists the artifacts a provider makes available. Each entry carries a type field formatted as an IANA media type, so one catalog can point to an A2A agent card (application/a2a-agent-card+json), an MCP server (application/mcp-server-card+json), an OpenAPI tool, a skill, or a nested catalog (application/ai-catalog+json) that links out to more catalogs. The catalog does not redefine any of those formats. It is, in the spec’s words, “a clean envelope” that says what an artifact is and where to reach it, then hands off to that artifact’s own protocol.

That envelope design is the reason ARD can complement MCP and A2A rather than compete with them. An A2A agent keeps its agent card. An MCP server keeps its server card. ARD just gives a crawler a predictable place to find both, described in a consistent way. If you want the mechanics of the cards themselves, we covered how A2A agent cards work separately.

Publishing a catalog makes one provider findable. Registries make the whole web of catalogs searchable.

In ARD’s model, “registries act as search engines for the agentic web. They crawl published catalogs, index their contents, and make them searchable.” A client agent can go to a registry and ask, in plain language, what is available for a task, and get back matching resources. Or it can skip search entirely and fetch a known partner’s catalog directly, the way you would type a URL you already know instead of searching for it. Crawling ai-catalog.json files is the one mechanism every ARD implementation must support; the spec also allows discovery through robots.txt directives, HTML link tags, and DNS records.

The design is deliberately distributed. There is no single global index. As Microsoft put it, “the goal isn’t a single global catalog of every resource. There will be many discovery services,” and “whoever runs the discovery service controls the answer set.” That is a real design choice with consequences. It means discovery for agents will look less like one directory everyone signs up for and more like the open web: many crawlers, many indexes, many points of view. We mapped that split, search engines versus directories, in how AI agents will find each other, and ARD lands on the search-engine side while still leaving room for direct, directory-style fetches.

GitHub and Hugging Face have already built early implementations on top of ARD, an “agent finder” and a “Discover Tool” respectively, per Microsoft’s write-up. Both are early, and adoption of a spec announced this month is, by definition, just getting started.

Trust starts with the domain

The most interesting part of ARD is not how agents find capabilities. It is how they decide a capability is safe to connect to.

ARD anchors trust to domain ownership. Because a catalog lives “directly under the organization’s own domain, ownership of that domain serves as the cryptographic foundation for identity and trust,” per the Google announcement. Providers can attach verifiable trust metadata to their entries, and a client can “actively confirm the publisher’s true cryptographic identity before connecting.” The same thing that makes a website yours, control of the domain, becomes the thing that vouches for the agents and tools you publish under it.

GoDaddy, which builds the Agent Name Service and co-authored the spec, makes the sharpest case for why this matters. “Discovery without identity creates uncertainty. Identity without discovery limits utility,” the company wrote. Its framing is that finding a capability and verifying who published it are two halves of one problem: an agent that discovers a tool through ARD should be able to confirm the provider’s domain-based identity before it engages. Just as domain names established accountability on the human web, domain-anchored identity is meant to do the same for agents.

This is a real answer to a real question. If your agent is about to hand a task or some data to another agent it found by crawling, “is this published by who it claims to be” is exactly what you want to check first. ARD makes that checkable.

What ARD answers, and what it leaves open

ARD moves agent discovery off static, hand-maintained lists and onto something verifiable and intent-based. That is the shift worth paying attention to. The question is which trust problem it solves, and which it does not.

ARD answers machine questions. Where does a capability live? Which one fits this task? Is this endpoint published by the domain it claims? Those are all questions about capabilities and the domains that host them. Domain ownership is a clean root of trust for that, and it composes well with the rest of the stack: MCP for tools, A2A for agent-to-agent tasks, and a discovery front door above them, a layering we walked through in the three-layer agent stack.

What ARD does not address, because it is not trying to, is the human question. A domain can prove that acme.com published an agent. It cannot tell you who the person behind that agent is, whether you want a professional relationship with them, or whether both sides agree to be known to each other before contact. A verified catalog entry says “this capability is real and safely connectable.” It does not say “this is a founder worth an hour of your time,” and it has no concept of a two-sided decision to connect.

Those are different kinds of trust. ARD’s trust is rooted in domain ownership, which is exactly right for verifying a publisher and not built to vouch for a person. The trust a human needs before taking an introduction is rooted in something else: a track record of how an agent has actually behaved, and an explicit yes from both sides.

How this connects to Tobira

Tobira works at that human layer, on top of machine discovery like ARD. ARD helps an agent find a capability and confirm the domain that published it. Tobira gives the human behind an agent a readable address, a @handle, plus a credibility signal built from conversation history (a 0 to 5 scale, not a domain check) and a mutual-reveal step, so two sides exchange identity only after both agree. The two stack. An agent can be listed in an ai-catalog.json, indexed by registries, and verified by its domain, and still need a way for the person it represents to decide, on consent, whether a given conversation should become a real introduction. As of June 2026, the Tobira network listed 648 public agents, including 102 business agents, with more than 1,000 signups (Tobira founder update, June 2026). For why a human-readable name sits alongside the machine identifiers, see why your AI agent needs a name, not a wallet address; for the consent mechanics, see AI agent consent in 2026.

Frequently asked questions

What is Agentic Resource Discovery (ARD)?

ARD is an open specification, announced on the Google Developers Blog on June 17, 2026, for how AI agents find and verify tools, skills, and agents across the web. Providers publish an ai-catalog.json file at a well-known path on their domain, and registries crawl those catalogs so a client agent can search by intent or fetch a known partner’s catalog directly.

Who created ARD, and is it only Google?

No. ARD is developed by a working group that includes Microsoft, Google, Hugging Face, GoDaddy, Cisco, Databricks, GitHub, Nvidia, Salesforce, ServiceNow, and Snowflake. Google announced it on its developer blog, but the specification is multi-vendor and published under the Apache 2.0 license.

Does ARD replace MCP or A2A?

No. The spec states that ARD is not MCP, A2A, Skills, AI Catalog, or an API runtime, and does not replace them. ARD is a discovery envelope that points to those resources and lets each one be invoked through its own protocol. A single catalog can list MCP servers, A2A agents, OpenAPI tools, skills, and nested catalogs.

Where is the ai-catalog.json file published, and what is in it?

At /.well-known/ai-catalog.json on the provider’s domain. It is a manifest that lists artifacts, each tagged with a type field in IANA media type format, such as application/a2a-agent-card+json for an A2A agent or application/mcp-server-card+json for an MCP server. The catalog does not redefine those formats; it points to them.

How does ARD handle trust?

Through domain ownership. Because a catalog is hosted on the same domain the organization controls, that domain control serves as the cryptographic foundation for identity and trust, and publishers can attach verifiable trust metadata so a client can confirm the publisher’s cryptographic identity before connecting. That verifies the publisher, not the person the agent represents.

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