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

Enables MCP clients to inspect and operate Kubernetes clusters across multiple contexts, with read-only/read-write/admin access modes and security flags controlling namespaces, contexts, deletes, applies, and exec.

Enables AI assistants to interact with Kubernetes clusters through 50 specialized tools for comprehensive cluster management. Supports both local kubectl and remote SSH-based execution for managing pods, deployments, services, and other Kubernetes resources.

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.

A lightweight MCP server that enables natural language interaction with Kubernetes clusters, allowing management of pods, deployments, namespaces, and cluster resources through conversational queries or API endpoints.

Enterprise-grade MCP server for Kubernetes operations, supporting local kubeconfig and AWS EKS authentication, with read, write, and destructive operations protected by multi-layer safety guards.

Provides read-only access to Kubernetes clusters for AI assistants.

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.

Enables secure Kubernetes operations with configurable security modes, supporting core Kubernetes resources, Istio service mesh, and Helm chart management through natural language.

Enables comprehensive Kubernetes cluster management through kubectl operations and Helm chart management. Supports resource operations, logging, scaling, rollouts, and diagnostics with multiple transport modes and security features.

Enables safe, read-only interaction with Kubernetes clusters, allowing users to list resources and fetch logs without any create/update/delete operations.

TypeScript implementation of Kubernetes cluster operations for pods, deployments, services.

A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with your AWS environment. This allows for natural language querying and management of your AWS resources during conversations. Think of better Amazon Q alternative.

Runs on Cloudflare Workers to let MCP clients execute AWS API commands with your own credentials via SigV4-signed HTTPS requests. Supports common S3, EC2, IAM, Lambda, and STS operations plus a generic escape-hatch for any AWS API call.

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.

This MCP server provides tools for inspecting AWS cloud infrastructure, including listing S3 buckets, EC2 instances, and fetching CloudWatch logs using your local AWS credentials.

MCP server for AWS SSO authentication and profile management, enabling AI assistants to check identity, switch profiles, and manage EC2/EKS resources.

A powerful and flexible Kubernetes MCP server implementation with support for OpenShift.

An MCP server for managing AWS ECS clusters, services, tasks, and container logs. Enables AI assistants to perform operations like scaling, deployments, and log retrieval via natural language.

Enables AI agents to provision and terminate AWS EC2 instances using natural language commands.