Original article excerpt
Server-side extracted preview paragraphs from the original source.
This post shows you how to deploy a serverless MCP proxy on Amazon Bedrock AgentCore Runtime that gives you a programmable layer to implement proper governance, controls, and observability aligned with an organization's security policies.
When AI agents connect to tools through the Model Context Protocol (MCP), they gain access to capabilities that range from database queries and API calls to file operations and third-party service integrations. In production, these interactions need proper governance, controls, and observability aligned with an organization’s security policies. This includes sanitizing tool inputs before they reach backend systems, generating audit trails in specific formats, or redacting sensitive data at the protocol layer. These requirements are shaped by internal governance standards, industry regulations, and the specifics of each production environment. This post shows you how to deploy a serverless MCP proxy on Amazon Bedrock AgentCore Runtime that gives you a programmable layer to implement these controls.