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

Connects to Elasticsearch clusters through the Model Context Protocol, enabling natural language querying and management of Elasticsearch data. Provides tools to search indices, list available indices, and retrieve index mappings.

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

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.

A Model Context Protocol server for Elasticsearch, enabling search, index inspection, and cluster information tools with optional write tools.

Provides comprehensive tools for managing Elasticsearch clusters, including security management, search operations, and index administration. It enables users to monitor cluster health, handle InfoSec tasks, and execute complex queries using Elasticsearch Query DSL and ES|QL.

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.

Small production-oriented MCP server for diagnosing incidents from Elasticsearch logs with unknown schema. It provides tools for log discovery, retrieval, and issue diagnosis.

A Python MCP server that provides AI agents with a controlled, read-first interface to Elasticsearch, Kibana Security, Fleet, and Elastic Defend.

A Model Context Protocol (MCP) server that provides safe, read-only access to Kubernetes resources for debugging and inspection. Built with security in mind, it offers comprehensive cluster visibility without modification capabilities.

A Model Context Protocol server implementation that provides endpoints for wallet-based authentication, cluster management, and name registration services.

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

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.

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

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

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.

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.

An Elasticsearch-based AI memory system optimized for Chinese that enables persistent knowledge storage and complex entity relationship management via the Model Context Protocol. It features advanced semantic search using the IK analyzer and supports multi-zone memory isolation for specialized knowledge graphs.

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