Introducing the fully managed Amazon EKS MCP Server (preview)

Introducing the fully managed Amazon EKS MCP Server (preview) Amazon EKS MCP Server tools Getting started with Amazon EKS MCP Server Prerequisites Configuration Tool access levels Scenario 1: Upgrading an EKS cluster with conversational AI Checking upgrade readiness Upgrade readiness report Key benefits of using EKS MCP for upgrades Scenario 2: Deploying applications through natural language Key EKS MCP tools in action Deployment summary Scenario 3: Troubleshooting infrastructure issues Key EKS MCP tools in action Troubleshooting summary Enhanced EKS console experience with Amazon Q Integrated AI assistance Contextual intelligence Conclusion About the authors Learn how to manage your Amazon Elastic Kubernetes Service (Amazon EKS) clusters through simple conversations instead of complex kubectl commands or deep Kubernetes expertise. This post shows you how to use the new fully managed EKS Model Context Protocol (MCP) Server in Preview to deploy applications, troubleshoot issues, and upgrade clusters using natural language with no deep Kubernetes expertise required. We’ll walk through real scenarios showing how conversational AI turns multi-step manual tasks into simple natural language requests. Teams managing Kubernetes workloads require expertise across container orchestration, infrastructure, networking, and security. While Large Language Models (LLMs) help developers write code and manage workloads, they’re limited without real-time cluster access. Generic recommendations based on outdated training data don’t meet real-world needs. Model Context Protocol (MCP) solves this by giving AI models secure access to live cluster data. MCP is an open-source standard that lets AI models securely access external tools and data sources for better context. It provides a standardized interface that enriches AI applications with real-time, contextual knowledge of EKS clusters, enabling more accurate and tailored guidance throughout the application lifecycle, from development through operations. Earlier this year, AWS was one of the first managed Kubernetes service providers to announce an MCP server, within a few months of the release of MCP protocol. Customers could install this EKS MCP Server on their machines for EKS and Kubernetes resource management. This initial, locally installable version of EKS MCP Server enabled us to rapidly validate our approach and gather valuable customer feedback, which has directly shaped today’s announcement.