Agentic Resource Discovery

Simple Definition

Agentic Resource Discovery is an emerging specification for publishing, discovering, and verifying AI tools, agents, skills, connectors, and other resources across registries.

The goal is simple: as the number of AI tools and agents grows, both people and AI systems need a standard, safer way to find the right resource for a task instead of relying on random, unverified integrations.

What It Aims to Do

• Let tool and agent makers publish resources in a standard format
• Let agents and teams discover the right tool for a task
• Help users verify that a resource is trusted before using it
• Work across federated registries rather than one closed catalog

Example

An AI agent could use a discovery system to find a verified tool for searching documentation, instead of guessing or wiring up a random untrusted integration.

A Note on Accuracy

Agentic Resource Discovery has been announced as an open specification, but the details are evolving quickly. Treat specific product or vendor claims as something to confirm against the official announcement before relying on them.

Related Terms

• Agent Registry, where discoverable resources are listed
• AI Agent Infrastructure, the layer discovery belongs to
• MCP Connector, a common type of discoverable resource
• AI Agent, the systems that use discovery
• Related guide: What are MCP connectors