AWS Agent Registry enables dynamic tool discovery for enterprise AI agents

<p>Amazon Web Services (AWS) has introduced AWS Agent Registry, a managed service designed to simplify the management of tools and capabilities for AI agents. The service provides a centralized catalog where developers can register Model Context Protocol (MCP) servers, agents, and specific agent skills, enabling orchestrators to discover and use these tools dynamically at runtime.</p><h2>Addressing the challenges of hardcoded toolsets</h2><p>In complex enterprise environments, managing AI agents often involves hardcoding tools into an orchestrator. As the number of internal APIs for functions such as pricing, inventory, or customer support grows, this traditional approach can lead to significant technical debt. Each addition typically requires code modifications, re-deployment, and coordinated releases across different teams. Furthermore, loading an extensive catalog into a model's context can lead to excessive token consumption and performance degradation.</p><p>AWS Agent Registry offers an alternative: an orchestrator can query the registry at runtime using natural-language requests to identify relevant tools. The system performs a hybrid keyword and semantic search, returning the necessary endpoint and descriptor information while excluding sensitive invocation credentials. This allows the agent to construct its toolset on a per-request basis, tearing it down once the task is complete.</p><h2>Governance and workflow</h2><p>The service incorporates a governed approval workflow to ensure only vetted capabilities are accessible. Records within the registry start in a 'DRAFT' status and must undergo a structured approval process to become available to the data plane. This allows organizations to separate the roles of capability publishers and administrators through Identity and Access Management (IAM) permissions.</p><p>The integration utilizes existing AWS infrastructure, including Amazon Bedrock AgentCore Gateway for hosting MCP servers and Amazon Bedrock AgentCore runtime for executing agent-to-agent (A2A) interactions. Authentication remains a separate, security-focused layer; the registry provides the connection metadata, but the application must manage authorization—such as Cognito OAuth tokens or IAM-signed Boto3 calls—through independent channels.</p><h2>Implications for enterprise AI</h2><p>By shifting from rigid, build-time wiring to dynamic discovery, development teams can publish and register capabilities independently, potentially reducing the release friction previously caused by monolithic orchestrator updates. While AWS notes that runtime discovery may not be necessary for every workload—particularly where capability sets are small and stable—the registry provides a path for enterprise-wide scalability as AI deployments grow in complexity and surface area.</p>

Source: aws.amazon.com
Original article: https://aws.amazon.com/blogs/machine-learning/discover-tools-at-runtime-with-aws-agent-registry/