"Managing Kubernetes Clusters on AWS Elastic Beanstalk" matching MCP servers:

MCP server that gives AI assistants full access to Kubernetes clusters and Helm, exposing 73 tools for managing pods, deployments, services, configs, secrets, logs, exec, port-forwarding, Helm lifecycle, and more.

Manages Kubernetes clusters through kubectl and Helm operations including pod cleanup, node management, and troubleshooting.

An MCP server that enables AI assistants to interact with Kubernetes clusters by translating natural language into kubectl and Helm operations. It allows users to query, manage, and diagnose Kubernetes resources and cluster states through a seamless integration.

An MCP server for generating Kubernetes manifests (deployments, services, configmaps, secrets, ingresses, namespaces) and performing kubectl operations like apply, delete, get, describe, logs, and exec.

A Model Context Protocol server allowing Claude AI to interact with AWS resources through natural language, enabling users to query and manage AWS services without using the traditional AWS Console or CLI.

Talk to AWS CLI from an MCP-speaking agent. Run any aws <service> <operation> command through the Model Context Protocol, with read-only defaults and gated write access.

Connects AI assistants to AWS infrastructure through AWS IAM Identity Center for secure, natural language management of cloud resources across multiple accounts. It enables users to execute AWS CLI commands, monitor resources, and run remote shell commands on EC2 instances via Systems Manager.

An MCP server that enables Claude to generate and execute AWS CLI commands, allowing users to manage AWS resources through natural language conversations.

A Python MCP server that lets MCP-compatible clients inspect and operate AWS through the AWS CLI, with command execution, suggestions, region lookup, and caller identity checks.

Enables creating and managing AWS EKS clusters via Terraform, including VPC, node groups, add-ons, and kubectl configuration.

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

Enables AI assistants to execute AWS CLI commands and retrieve service documentation through the Model Context Protocol. It supports Unix pipes for output filtering and provides pre-defined prompt templates for common cloud management tasks.

A Python CLI package aaws published to GitHub with PyPI distribution via GitHub Actions. Natural language in → AWS CLI command out, with explain, confirm, and safety layers. Available as MCP server.

Enables LLMs like Claude to securely execute Kubernetes CLI tools (kubectl, helm, istioctl, argocd) across multiple clusters through dynamic kubeconfig support, allowing natural language Kubernetes management and operations.

A Docker-based MCP server that enables Claude to run Kubernetes CLI tools (kubectl, istioctl, helm, argocd) in a secure containerized environment for managing and troubleshooting clusters.

Provides a set of tools to interact with Tecton clusters, manage feature stores, and execute Tecton CLI commands through the Mission Control Protocol.

Infrastructure access broker for AI agents — SSH & Kubernetes. Per-operation ephemeral credentials minted by a separate signer; the model never touches one. MCP stdio / HTTP+OIDC.

SSH MCP is a Model Context Protocol tool for managing and interacting with multiple virtual machines over SSH. It simplifies executing commands on remote servers using the standard SSH config file format.

Durable MCP server for managing long-running jobs locally, over SSH, or on Slurm clusters. Jobs survive client disconnects and return exit codes, bounded logs, and JSON artifacts.

Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.