"Design Resources and Prototyping Best Practices" matching MCP servers:

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

A minimal MCP server for UW Hyak (klone) that exposes tools to run shell commands and write files remotely, along with documentation resources for klone-specific utilities.

A production-ready MCP server that enables AI assistants to execute shell commands, manage files, monitor system resources, and automate complex workflows with advanced features like stock tracking and web automation.

MCP server for managing Proxmox VE resources, VM/CT lifecycle, snapshots, backups, and clones via natural language.

A Model Context Protocol server that allows language models to manage Hetzner Cloud resources through structured functions, including servers, volumes, firewalls, and SSH keys.

Enables managing Google Cloud Platform resources through natural language commands in Claude Desktop, supporting comprehensive operations across compute, storage, databases, networking, monitoring, and IAM without manual credential setup.

Enables intelligent interaction with Azure resources through natural language by translating requests into safe, auditable Azure CLI commands with plan/review workflows and direct access to 8 Azure services including Storage, Cosmos DB, Key Vault, and more.

MCP server for running shell commands on a Linux development board via UART serial.

An educational MCP server exposing shell command execution (PowerShell and sh) and a benign tool for learning about MCP tools, resources, and security risks like tool poisoning.

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.

Manages AWS, Azure, and Hetzner Cloud resources, and executes remote SSH commands via MCP integration.

Enables AI agents to monitor system resources and control media, brightness, volume, and other Windows PC functions through natural language commands.

Enables agent clients to safely connect to tools and execution resources through MCP with authorization, approvals, audit, chat-context isolation, SSH/Docker access, and long-running command session tracking.

Enables AI assistants to execute AWS CLI commands and access AWS documentation, resources, and prompt templates through the Model Context Protocol with support for Unix pipes and secure Docker-based deployment.

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.

Enables interaction with Google Cloud Platform services through gcloud CLI commands via a Cloud Run deployed MCP server. Supports executing gcloud commands and managing GCP resources through natural language.

A comprehensive MCP server that provides system troubleshooting and diagnostic tools, enabling LLMs to diagnose system issues, monitor resources, check logs, and test connectivity.

An MCP server that enables interaction with Kubernetes resources through natural language interfaces like Goose CLI, allowing users to get, read, and patch Kubernetes resources.

A Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.

A terminal emulator MCP server specifically engineered for LLMs with block-oriented design that organizes command input/output into recognizable blocks and semantic session management. Enables AI to efficiently use terminals for writing code, installing software, and executing commands without context overflow.