{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/16"}],"enrichment":{"capability":"Connects AI code assistants to Amazon EKS clusters via the Model Context Protocol, enabling LLMs to create clusters, deploy applications, manage Kubernetes resources, and troubleshoot issues through natural language.","skillfed_tags":["mcp-server","eks-kubernetes","ai-assistant-integration"],"use_cases":["Provision new EKS clusters with prerequisites (VPCs, subnets, networking) by translating natural language into CloudFormation templates.","Deploy containerized applications to existing EKS clusters by applying user-provided Kubernetes YAML or generated manifests.","Perform full lifecycle operations on Kubernetes resources through natural language queries in your IDE's AI assistant.","Retrieve pod logs and Kubernetes events for troubleshooting and monitoring without leaving your code editor.","Streamline cluster setup by having an AI assistant apply best practices and handle prerequisite creation automatically."],"what_it_does":"This package is an MCP (Model Context Protocol) server that bridges AI code assistants to Amazon EKS clusters. It translates natural language requests from LLMs into AWS and Kubernetes API calls, enabling AI assistants to perform cluster operations without requiring users to write infrastructure code directly.\n\nThe server supports the full lifecycle of EKS management: creating new clusters with VPCs and networking via CloudFormation, deploying containerized applications from YAML or generated manifests, managing individual Kubernetes resources (create, read, update, patch, delete), listing and filtering resources by namespace or labels, retrieving pod logs and events, and troubleshooting cluster issues. It requires Python 3.10+, AWS credentials, and appropriate IAM permissions; Kubernetes API access is controlled by either IAM access entries or kubeconfig credentials depending on your authentication mode.","worth_installing":"Yes, if you use Cursor, Kiro, or VS Code with AI assistants and need to manage EKS clusters from within your IDE. The package is actively maintained, has no known vulnerabilities, and low install friction. Requires careful IAM permission management in production\u2014read-only mode is safe for exploration, but write operations demand restrictive policies and trusted environments. Not applicable if you don't use an MCP-compatible AI assistant."},"id":"awslabs-eks-mcp-server","links":{"html":"https://skillfed.io/packages/awslabs-eks-mcp-server","md":"https://skillfed.io/packages/awslabs-eks-mcp-server.md","pypi":"https://pypi.org/project/awslabs-eks-mcp-server/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"awslabs.eks-mcp-server","python_support":"supports_current","summary":"An AWS Labs Model Context Protocol (MCP) server for EKS"},"popularity":{"monthly_downloads":123837,"position":11897,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.37"}