AWS's New Tool Registry Lets AI Agents Find Their Own Tools
This could make AI assistants smarter and faster at handling your requests.
AWS Agent Registry is a managed service for cataloging and discovering Model Context Protocol servers, agents, and agent skills. It addresses a problem that agent demos might hide: hardcoded tools work for a handful, start to degrade at a few dozen, and become unmanageable beyond that, especially in enterprise systems that expose hundreds of internal APIs for pricing, support, orders, inventory, and customer data.
In these systems, the model can spend more tokens disambiguating tool names than reasoning about the user’s request, and each new capability requires an orchestrator code change, a redeploy, and a coordinated release across teams. One approach is to change how the orchestrator accesses its tools: instead of compiling every tool into the agent, the agent can discover relevant tools at runtime.
At runtime, an orchestrator can search approved, discoverable records and use the returned endpoint and descriptor content to construct a client. Registry search results do not return the capability’s invocation credentials or authentication scheme; the application must obtain and apply appropriate credentials through a separate, trusted configuration path. The sample walks through a Discover, Instantiate, Execute loop with an order-management MCP server through Amazon Bedrock AgentCore Gateway, two agent-to-agent agents on AgentCore runtime, a Registry, and an orchestrator.
- AWS Agent Registry lets AI agents search for tools at runtime, like a live directory.
- This reduces the need for manual coding and redeployment when new tools are added.
- It could lead to faster, more accurate AI assistants for tasks like customer service and order processing.
Why It Matters
This makes AI assistants more adaptable and accurate, so you get better service without waiting for updates.