Eleven companies — Google, Microsoft, GitHub, Hugging Face, NVIDIA, Salesforce, Snowflake, Cisco, Databricks, GoDaddy, and ServiceNow — have published the Agentic Resource Discovery specification, a draft open standard under Apache 2.0 for how AI agents find and verify tools, skills, MCP servers, and other agents across the web. The mechanism is intentionally familiar to anyone who has shipped a robots.txt or sitemap: a provider hosts an ai-catalog.json at a known path on its domain, describing the resources it exposes and how an agent client should connect. Registries crawl those catalogues and let agents query them by capability.
The problem ARD targets is the wiring tax of current agent stacks. Today, every tool, API, or MCP server an agent uses must be pre-registered in the agent's configuration. That worked when an agent had five integrations. It does not work in a world where every SaaS vendor, internal service, and skill marketplace exposes its own agent surface. ARD moves discovery to runtime — the agent asks 'who can do X,' a registry answers with verified candidates, and the agent connects. Reference implementations are already out: GitHub shipped 'agent finder' inside Copilot, and Hugging Face published a Discover Tool that searches across ARD services.
ARD is also a political document. The launch coalition is notable for who is in it and who is not — OpenAI and Anthropic are absent from the initial signatories, even though both ship the MCP and tool-use surfaces ARD is designed to index. That likely reflects vendor preference for first-party registries (OpenAI's GPT Store, Anthropic's MCP directory) over a neutral standard. Whether ARD becomes the discovery layer or one of several depends on how aggressively the big agent platforms federate to it. The Apache 2.0 license is the right starting move; the question is adoption.
A takeaway for learners: if you build anything an agent might want to call — an API, a database connector, a domain skill — read the ARD spec and consider publishing an ai-catalog.json. The cost is low, the upside is being discoverable by the next generation of agent clients. If you study standards, this is a textbook case of incumbents trying to head off fragmentation by writing the protocol before anyone has the leverage to impose one. Watch whether OpenAI or Anthropic join.