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    Enables users to interact with container registries through the ORAS CLI, providing information about container images, platforms, and signatures via natural language queries.
    7
    Apache 2.0
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    This MCP provides comprehensive tools and resources for MSX software development, testing, and automation through openMSX emulator.
    73
    GPL 2.0
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    A Model Context Protocol (MCP) server that interfaces with the Apache YuniKorn Scheduler, allowing AI agents to observe and reason about Kubernetes batch workload resource management, queue hierarchies, and application states.
    7
    10
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    A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.
    69
    MIT
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    Enables programmatic control and AI-driven E2E testing of iOS virtual machines by exposing display, touch input, and navigation tools. It provides hardware key emulation, app navigation, and raw touch interactions with inline screenshot feedback for real-time visual context.
    17
    82
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    An MCP server that provides AI agents with a full Ubuntu desktop environment inside Docker, enabling them to perform complex computer tasks like browsing, coding, testing, and GUI automation.
    36
    9
    MIT
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    Enables plain English queries about VMware vCenter environments including clusters, VMs, datastores, and more, directly from VS Code via GitHub Copilot.
    33
    59 PyPI
    MIT
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    Enables AI-powered management of Ludus cyber range environments through natural language commands. Provides 157 tools for range lifecycle management, scenario deployment, template creation, Ansible role management, and SIEM integration for security testing and research.
    100
    84
    MIT
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    A Python-based server that enables AI assistants to interact with an Unraid server through the official Unraid GraphQL API, providing read-only access to system information, Docker containers, VMs, storage, and more.
    130
    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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