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Agentic Resource Discovery

GitHub stars: 471 GitHub forks: 65 Declared license: Apache-2.0: Apache-2.0 Last pushed September 12, 2026: Pushed 14d ago
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Agentic Resource Discovery, or ARD, is a draft specification for publishing, discovering, and searching agentic resources such as MCP servers, A2A agents, Skills, APIs, and workflows.

The current v0.91 proposal puts ARD entries in domain-hosted /.well-known/ard.json manifests or other advertised sources, then lets registries search them before a client uses the selected resource through its native mechanism. The older ai-catalog.json path remains an optional compatibility source. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.

What it is

A discovery layer for agent resources

ARD gives publishers a way to describe callable AI resources and gives registries a common search interface for returning matching capabilities before a client connects to the chosen tool or service.

Why it stands out

Discovery stays separate from invocation

ARD proposes a common way for registries to find and return agent resources while leaving credentials, permissions, safety checks, and execution to the systems that connect to them.

Availability

Draft spec plus implementation trail

Readers can inspect the ARD specification site, the public GitHub spec repository, Google and Hugging Face launch posts, and Hugging Face Discover as a working ARD client and server implementation.

Why it matters

What makes it useful

Agentic Resource Discovery tackles the step before an agent invokes a tool: how MCP servers, A2A agents, Skills, APIs, and workflows can be published, searched, and checked. Its draft status and Hugging Face implementation show both the proposal and an early working path without treating the standard as settled.

Notable points

What stands out

The v0.91 proposal uses /.well-known/ard.json and rel="ard" links for domain discovery, with POST /search for registry queries; ai-catalog.json remains optional compatibility. Hugging Face Discover implements search over Hub Spaces, Agent Skills, and MCP servers through REST and MCP paths.

Before using

What to review

Current draft status, schema changes, issue discussions, conformance tooling, and repository updates before treating ARD behavior as settled.

Which registry or catalog is being queried, who operates it, what it indexes, and how its ranking, trust, and access policies work.

What publisher identity or trust metadata is actually present, and whether the client verifies it before connecting to a returned resource.

The native protocol, credentials, permissions, privacy terms, rate limits, and logging behavior of the resource after discovery hands off to invocation.

Whether ARD is being used alongside MCP, A2A, Skills, APIs, or internal catalogs rather than replacing those systems.

Reader fit

Who may find it relevant

Builders tracking how agents find tools, skills, and services across provider boundaries.

Teams comparing agent registries, internal catalogs, MCP servers, Skills, A2A agents, APIs, and trust metadata.

Builders who want a published specification and working reference implementation for testing discovery across agent formats.

Less relevant for readers looking for a finished consumer assistant, a model checkpoint, or a one-click decision about every returned tool.

Editorial note

Why LifeHubber lists it

ARD gives publishers a draft format for describing agent resources and registries a way to search for them. Builders can judge whether this could make their MCP servers, Skills, or APIs easier to find; credentials, permissions, and safety checks still depend on connected systems.

Source links

Source materials

Reader note

Before relying on this entry

LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.

What to explore next

Decide what happens after discovery returns a resource.

ARD helps a client find agent resources, then hands off to their native tools and protocols. These links cover reviewing a discovered skill and examining policy controls around later agent actions.

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