As your AWS infrastructure scales, operational workflows naturally grow more complex. SREs and DevOps Engineers spend significant time context-switching between the AWS Management Console, CLI documentation, and multiple service dashboards. They manually translate business questions into the correct API syntax, chain calls across services, and rebuild the same integration patterns for each new use case.This friction compounds over time. Incident investigations require cross-referencing Amazon CloudWatch Logs, Amazon Elastic Compute Cloud (Amazon EC2) instance states, and AWS Identity and Access Management (IAM) policies across separate interfaces. Capacity planning means manually querying multiple services and assembling results. Security audits demand consistent, repeatable API call sequences that are time-consuming to script from scratch.

This post shows you how to use Amazon Bedrock AgentCore Runtime with Model Context Protocol (MCP) support to connect Amazon Quick with AWS services through the AWS API MCP Server, creating a conversational AI assistant that translates natural language into AWS Command Line Interface (AWS CLI) commands, without the need to switch between tools during critical moments.