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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsAgentic Resource Discovery (ARD) is a way for AI clients to find capabilities—such as tools, MCP servers, agents, skills, APIs, and workflows—before deciding which one to use. It addresses a practical gap: clients may know how to invoke a capability once it is configured, but finding and evaluating the right capability across teams or organizations is often fragmented. ARD handles discovery; the selected resource is still invoked through its own protocol or API.
What problem does ARD solve?
An agent can only make useful choices from the capabilities it can identify. In many setups, people manually locate tools, assess their descriptions, wire them into an agent, and maintain those connections. Loading every possible capability description into an agent’s context is difficult to scale, while hard-coded lists limit what it can find.
ARD proposes moving the search step into a dedicated discovery service. A client can ask, in effect, “What agentic resource can help with this task?” and receive candidate resources with structured information to help assess them. The aim is to make capabilities discoverable without requiring every agent to have a complete, manually maintained list in advance.
What ARD does—and what it does not do
ARD is a discovery layer, not an execution runtime, a replacement for MCP, or one universal marketplace. It describes and helps locate resources; it does not redefine how those resources work internally. After discovery, the client connects using the selected resource’s native mechanism, which might be MCP, an API, a workflow system, or another protocol.
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There is no single global ARD answer set. Different registries can index different resources, rank results differently, and apply their own access and governance policies. An enterprise registry might focus on internal or approved capabilities, while a public service may cover a broader set.
How discovery works
At a high level, a publisher describes available capabilities in a catalog, and a registry ingests and indexes those descriptions so clients can search them. The catalog is the publisher’s description surface; the registry is the discovery and search service. Catalogs may be hosted under an organization’s own domain, as described in Google’s architecture announcement.
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Google’s announcement outlines a practical sequence. It is an architecture description, not a guarantee that every ARD implementation currently supports every stage in the same way.
- Publish: A provider makes a catalog describing its resources available.
- Discover: A client searches a registry or fetches a known catalog directly.
- Assess identity: The client uses trust metadata to help verify who publishes or operates a resource.
- Connect: Once selected and permitted, the client connects directly using the resource’s native protocol or API.
The registry’s search response helps a client decide what to inspect or use; it is not itself the call to the discovered resource.
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What the ARD proposal standardizes
The ARD specification repository lists version 0.91 as a proposal dated August 26, 2026. It describes an artifact-agnostic envelope for discovery: entries identify resource types and carry information relevant to finding and assessing them without replacing the internal schemas of MCP, A2A, or other protocols. The v0.91 proposal uses JSON-LD nodes and namespaces, while stating compatibility with earlier manifests.
For registry interoperability, the proposal requires an HTTP REST search interface. Namespaces can extend the description vocabulary. The proposal also notes that some media-type identifiers reflect de-facto community usage while IANA registration is pending, so builders should not assume every identifier is formally registered or frozen.
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ARD remains an evolving open specification, rather than a finalized standard deployed uniformly across products. The official project introduction describes ARD as a specification, not a product, and anticipates multiple discovery services implementing it.
Discovery metadata is not a trust decision
A useful entry can tell a client what a resource does, who provides it, where it is hosted, how it can be invoked, what inputs it accepts, and what authority it may require. That information can support relevance and identity assessment, but a search result alone does not establish that a resource is safe, suitable for a particular task, authorized for a user, or correctly implemented.
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Microsoft’s June 17, 2026 announcement emphasizes that ARD does not replace authentication, authorization, governance, or organizational trust decisions. Organizations still need their own policies and approval controls before enabling a discovered capability. Google’s description of trust metadata and secure direct connections likewise should not be read as a substitute for client-side verification and policy enforcement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Examples of ARD discovery services and registries
The following examples differ in audience, scope, and the maturity of the features described. Their names and capabilities reflect the cited announcements and project materials; availability and product naming can change.
| Service or project | What the cited source describes | Scope or qualification |
|---|---|---|
| GitHub Agent Finder | Microsoft’s launch article says it lets Copilot discover and call MCP servers, skills, tools, and agents at runtime. | The article describes public curated resources as well as private registries. |
| Hugging Face Discover Tool | Microsoft identifies it as a reference implementation offering semantic search across Hugging Face resources and other ARD discovery services. | Presented as a developer-facing discovery option, not as a universal registry. |
| Google Cloud Agent Registry / Gemini Enterprise Agent Platform | Google describes hosted search, discovery, and hosting for agentic resources, alongside enterprise governance and identity/trust features. | The announcement included future-availability language; check current rollout and product naming rather than assuming every announced feature is generally available. |
| AWS Agent Registry | AWS describes a centralized catalog for agents, MCP servers, tools, skills, and custom resources. | The AWS article presents cross-environment federation as an expected ARD benefit; distinguish that outlook from features the registry currently provides. |
| ANS Finder | The official ARD introduction identifies it as a self-hostable discovery service. | Self-hosting offers an ownership option; specific feature parity with other services is not stated in the introduction. |
How to evaluate an ARD option
Choosing a registry is not just a question of whether it can return search results. Compare what it indexes, how it governs access, and what operational responsibility it places on your organization.
- Coverage: Which resource types and publishers are indexed? Can it find the internal capabilities your agents need as well as any permitted external ones?
- Search quality: How are task descriptions matched to resources, and can you understand or control ranking?
- Federation: Does it search only its own catalog, accept known catalogs, or connect to other registries? Treat interoperability claims according to whether they are implemented or planned.
- Controls: What authentication, authorization, policy, approval, and publisher-verification mechanisms are available? Decide which controls must remain in your own client or organization.
- Ownership: Is the service hosted by a provider or self-hosted? Consider who maintains catalogs, indexing, access rules, and operational availability.
- Maturity: Is the implementation built against the evolving proposal, and what conformance or compatibility is documented? Separate current product behavior from specification goals.
When ARD is useful
ARD is most relevant when an agent needs to discover capabilities that are not all preconfigured, especially across teams, catalogs, or organizations. It offers a common way to describe and search for candidates while leaving execution and governance in the systems that own those responsibilities. For a small, fixed set of tools, a manually configured list may remain simpler; ARD’s value grows as capability inventories and discovery boundaries become harder to manage directly.
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