How Do AI Agents Discover Services?

Agent discovery is how an AI agent determines what capabilities, endpoints, authentication methods and protocols an organisation exposes — without prior configuration or human navigation. Instead of scraping a page written for people, the agent fetches a machine-readable document at a well-known path that names the organisation’s capabilities as verbs, its accountable human, its endpoints and its prices, so the agent knows what it can do before it does anything.

Input

A domain

Mechanism

A machine-readable well-known document

Capabilities as

Verbs, not departments

Standards still

Converging — no single ratified file yet

Discovery is not scraping

An agent should not have to reverse-engineer a marketing page to learn what an organisation offers. Discovery replaces interpretation with a declaration: a document the organisation publishes and stands behind. That is faster, more reliable, and — because it names an accountable human — more trustworthy than inference.

Discovery is a separate problem from identity and from authorization. Knowing what an organisation can do is not the same as knowing who you are talking to, or what you are permitted to ask of it. Good discovery keeps those concerns distinct.

Related standards

agents.txtA2A Agent CardMCP

Questions

Is there one standard discovery file?

Not yet. Several conventions coexist — well-known agent documents, agents.txt, agent cards. The space is converging, which is why a neutral, composable approach matters more than betting on one file.

Why not just let agents scrape?

Scraping is fragile, ambiguous and unaccountable. A declared interface is deterministic and names who is responsible for it.