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    A comprehensive Model Context Protocol (MCP) server that exposes 216 tools, 7 resources, and 10 runbook prompts for every OpenShift 4 cluster operation an SRE, developer, or operator could need — all driven by an LLM.
    216
    Apache 2.0
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    A multitenant Streamable HTTP bridge over Nutanix's Prism Central v4 API MCP server, enabling per-tenant credential forwarding and read-only tool operations.
    Apache 2.0
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    MCP server for building and driving VMware Workstation VMs from an AI agent, enabling unattended OS installs, guest command execution, file transfer, screenshots, and fleet management.
    35 npm
    2
    MIT
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    A powerful, lightweight Model Context Protocol (MCP) server built in Python that enables Artificial Intelligence assistants (Claude Desktop, Cursor, Antigravity, Claude Code, etc.) to manage and monitor your Proxmox VE cluster using natural language.
    MIT
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    MCP server for managing Docker containers, images, networks, volumes, and Compose projects via Arcane, exposing a single 'arcane' tool for read/write operations over stdio or HTTP.
    3
    AGPL 3.0
  • A
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    This MCP server enables answering vantage-relative reachability questions about a Docker host, resolving which service address works from the host, a named network, or a specific container. It reads live Docker runtime state and probes services to report the correct address or explain precisely why none is available.
    MIT
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    Docker Helper MCP server that provides tools for automating Docker tasks such as generating Dockerfiles, parsing docker-compose files, and optimizing images.
    18 npm
    33 PyPI
    MIT
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    Enables users to query Azure HPC/AI Kubernetes clusters for GPU node information and InfiniBand topology details through kubectl commands. Provides tools to list GPU pool nodes with their status and retrieve network topology labels for high-performance computing workloads.
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    Enables interaction with Google Kubernetes Engine (GKE) to list clusters, manage node pools, and retrieve server configurations. It includes automated scripts for deploying and testing sample applications across multiple GKE Autopilot clusters.
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