AI Agent Registries: Inventory Before Scaling

With AWS Agent Registry, a central catalog for agents, MCP servers, tools and skills is now generally available. Google Cloud documents a similar registry in Gemini Enterprise Agent Platform, while Microsoft consolidates agents in the Microsoft 365 admin center. This creates a new operational requirement: enterprises need to inventory agents like other production IT assets before scaling their use.

From prototype to discoverable asset

AWS describes two separate planes. The governance plane is intended to cover all registered resources, including metadata, access and lifecycle state. The discovery plane contains only curated and approved records. The catalog supports agents, MCP servers, skills and custom JSON-based resource types; semantic search is designed to make existing capabilities discoverable.

Google follows the same principle. Its registry manages agents, MCP servers, endpoints, skills, skill revisions and publishers, among other resources. It can centralize metadata across several cloud projects. Microsoft adds summary metrics for agents without owners and for unmanaged agents. That distinction shows why registration alone is not yet governance.

The metadata that matters

A reliable agent registry should answer at least five questions:

Owner: Which business and IT roles are accountable for purpose and operation?
Version: Which agent, skill and tool version has been approved?
Authority: Which data, endpoints and actions may the agent access?
State: Is the record a draft, reviewed, productive, blocked or retired?
Evidence: Where are the security review, usage signals, changes and expiry date?

This helps prevent duplicate development and ownerless agents. It also connects the software catalog, identity management, API governance and operational monitoring. Semantic search is useful, but the decisive question is whether a discovered component has a responsible owner and a current approval state.

What this means for DACH enterprises

AWS lists Europe (Ireland) as an available region for its registry. That does not replace a privacy assessment or data classification: a European catalog does not determine where model calls, logs or connected business data are processed. Region, data class and legal basis therefore need to be explicit metadata fields.

Start with an inventory across cloud platforms, Copilot Studio, developer repositories and existing MCP servers. Flag unknown owners and unused records as findings. Only then should automated discovery or reuse be enabled. The objective is not the longest list of agents, but a registry in which every production record is discoverable, accountable and capable of being retired.