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

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.

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.

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.

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

A small AWS MCP for AI assistants: one server, one config entry, SSO re-auth baked in, generic CRUD over hundreds of resource types, live docs lookup, server-side scripting for batched workflows.

Enables AI assistants to manage Docker containers and Kubernetes resources through natural language, supporting operations like container management, image building, and pod/deployment/service management.

Enables management and provisioning of AWS resources like EC2, S3, and RDS using natural language prompts through the Model Context Protocol. It allows users to automate complex infrastructure tasks, such as setting up VPCs and security groups, via a chat interface.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

A unified MCP server for AWS that enables natural language infrastructure management, cross-service resource discovery, and dependency mapping. It features 30 intelligent tools for cost optimization, incident investigation, and multi-account operations protected by a robust safety system.

Provides Kubernetes cluster management capabilities through natural language via MCP protocol over HTTP/SSE. Supports Pod, Service, Deployment operations, log retrieval, and resource management with JWT authentication and RBAC permissions.

Enables AI assistants to interact with AWS services and resources through AWS CLI commands, allowing management of AWS infrastructure with security controls.

A read-only MCP server for safe, structured investigation of AWS serverless resources, providing curated tools for tracing dependencies, permissions, and failures without exposing raw SDK access.

Enables interaction with AWS services (EC2, S3, Lambda, DynamoDB, etc.) through the Model Context Protocol, allowing natural language management of cloud resources.

MCP server deployed on EdgeOne Pages, providing a Streamable HTTP MCP server for intelligent chat applications with tool capabilities like generating webpages.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

Enables users to generate professional AWS architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python code through the diagrams package. Supports customizable styling and secure diagram generation for cloud infrastructure visualization.