Agentic Resource Discovery Specification (ARD)

Canonical version: Agentic Resource Discovery Specification (ARD).

Agentic Resource Discovery (ARD) is an open, draft specification (Apache 2.0 License) for publishing, discovering, and verifying AI capabilities across the web. It's a collaborative effort, not one vendor's project: contributors come from Google, Microsoft, Hugging Face, GoDaddy and others. It answers the question an agent needs before it can act: where do capabilities exist, which one should I use, and is it safe to connect to. A client cannot use a capability it does not know exists, and today there is no standard way to answer that across organizations.

ARD sits before invocation. It helps a client decide which capability to use; the actual call still happens through that resource's own mechanism (MCP, an API, an agent framework, a workflow system). The discoverable "agentic resources" include tools, Skills, MCP servers, APIs, workflows, and other agents.

How it works

• Catalogs: an organization publishes an ai-catalog.json file at a well-known path on its domain, describing its capabilities. Domain ownership is the cryptographic basis for identity and trust.
• Registries: Agent Registries are search engines for the agentic web that crawl and index published catalogs, so agents can query for capabilities with verifiable trust metadata.
• Flow: publish a catalog, discover via a registry or a direct fetch, cryptographically verify the publisher's identity, then connect directly using the resource's native protocol.

Parts of the specification

I've broken the spec down into atomic notes, one per part:

• AI Catalog (ai-catalog.json) — the static manifest a publisher hosts, and the entries inside it
• ARD URN Identifier — the domain-anchored urn:air: name that gives every resource a stable, trust-carrying identity
• ARD Discovery Mechanisms — the four ways (well-known URI, Agentmap, HTML link, DNS) a catalog gets found
• Agent Registry (ARD) — the dynamic search layer and its REST API (/search, /explore, /agents)
• ARD Federation — how registries cooperate so no single index has to hold everything
• ARD Trust Manifest — verifiable identity, attestations, and provenance, plus the declare-vs-verify trust model

Context

• Builds on the Linux Foundation's AI Catalog data model; supports MCP servers, OpenAPI tools, A2A agents, and nested catalogs as discoverable resources
• A spec, not a product: multiple discovery services can implement it (e.g. GitHub's Agent Finder, Hugging Face's Discover)
• Hugging Face's Discover is the most concrete reference registry so far. It already indexes thousands of Skills, ML apps and MCP servers from the Hub and other ARD services, reusing the Hub's existing semantic search, and exposes both a REST POST /search endpoint and an MCP endpoint at huggingface-hf-discover.hf.space
• Google Cloud's Agent Registry (Gemini Enterprise Agent Platform) is adding native ARD support
• Think of it as robots.txt / sitemaps for agent capabilities rather than web pages

My Opinion

This specification will definitely matter. It's backed by big players, and it has strong potential. One of the challenges people who create/use/leverage more and more agentic resources (AI Skills, MCP servers, AI agents, etc) is that those fill-up the AI context window really quickly and end up confusing AI models & agents. I've fought against this problem by organizing skills in categories, optimizing skill descriptions, tagging those, etc. When building MCP servers, I've used the Code Mode MCP Pattern, which helped, but only solved a part of the problem.

With over 500 AI Skills in my own system (cfr Obsidian Starter Kit), this really became a problem.

With this new specification, we finally have a standard way to add indirection. Instead of directly installing/registering MCP servers, AI Skills & agents, we can instead add them to a catalog, and let our agentic tools discover and use those when needed/relevant.

References

• https://agenticresourcediscovery.org
• https://agenticresourcediscovery.org/introduction/
• https://agenticresourcediscovery.org/ai_catalog_spec/
• https://agenticresourcediscovery.org/how_to_publish/
• https://developers.googleblog.com/en/announcing-the-agentic-resource-discovery-specification/
• https://huggingface.co/blog/agentic-resource-discovery-launch
• https://github.com/ards-project/ard-spec
• https://github.com/ards-project/
• https://news.ycombinator.com/item?id=48573268

Related

• AI Catalog (ai-catalog.json)
• ARD URN Identifier
• ARD Discovery Mechanisms
• Agent Registry (ARD)
• ARD Federation
• ARD Trust Manifest
• AI Agents
• Agentic Engineering
• Model Context Protocol (MCP)
• Code Mode MCP Pattern
• OpenAPI Specification
• Large Language Models (LLMs)
• Apache 2.0 License

About Sébastien

I'm Sébastien Dubois, and I'm on a mission to help knowledge workers escape information overload. After 20+ years in IT and seeing too many brilliant minds drowning in digital chaos, I've decided to help people build systems that actually work. Through the Knowii Community, my courses, products & services and my Website/Newsletter, I share practical and battle-tested systems.

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