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    A Model Context Protocol server that enables AI assistants to interact with Kubernetes clusters through natural language, supporting core Kubernetes operations, monitoring, security, and diagnostics.
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    More than just a fully featured MCP server that lets AI agents manage Docker — containers, images, networks, volumes, swarm services, secrets, configs, nodes, plugins, etc., it helps you create workflows to easily manage your Docker environments.
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    More than just an MCP server that covers the entire range of Docker management tasks, it helps you create workflows to easily manage your Docker environments at scale. It allows you manage multiple local or remote (TCP, TLS, SSH) docker instances and exposes things like logs and stats as resources so that you can monitor and triage all of them.
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    VMware workflow orchestration — multi-step state machine with approval gates, audit logging, and conditional execution. Coordinates cross-skill workflows like clone-and-test or compliance-scan-and-remediate across the VMware MCP skill family.
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    Manages and views virtual machines across multiple cloud providers (AWS, Azure, Alibaba Cloud). Enables AI assistants to list, inspect, and control VMs through a unified MCP interface.
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    Provides a local, isolated Linux VM sandbox for AI agents using Apple's Virtualization.framework, enabling fast command execution (~60ms) and package management without cloud costs.
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    Manage Docker infrastructure across multiple homelab hosts including Unraid, Proxmox, and bare metal servers. Enables container lifecycle management, log retrieval, resource monitoring, and Docker operations across your entire homelab from a single interface.
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    An MCP server that enables AI assistants to manage Docker containers, images, networks, and volumes through a standardized interface. It supports comprehensive operations like container lifecycle management and image pulling while ensuring correct handling of command and environment variable arrays.
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    Enables AI agents to connect to and control a Virtual Private Server via SSH. It provides a comprehensive suite of tools for remote file system operations, session management, and shell command execution.
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    Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9
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