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    Exposes vLLM capabilities to AI assistants, enabling chat completions, model management, and platform-aware container control with automatic detection of Docker/Podman and GPU availability across Linux, macOS, and Windows.
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    Apache 2.0
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    Enables conversational management of Naver Cloud Platform infrastructure through Claude Desktop, allowing users to create, query, and manage cloud resources like servers, VPCs, load balancers, and databases using natural language.
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    A template MCP server that provides a basic structure and configuration for building Model Context Protocol servers. Includes Docker support, environment configuration, and examples for both STDIO and SSE transport modes.
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    An MCP server that enables seamless management of Novita AI platform resources, currently supporting GPU instance operations (list, create, start, stop, etc.) through compatible clients like Claude Desktop and Cursor.
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    MIT
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    MCP server that exposes fleet-aware KVM primitives for AI agents to control TinyPilot devices, including screen capture, keyboard input, mouse events, and device selection.
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    MIT
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    Enables AI clients to control an Android emulator via MCP, allowing tasks like tapping, typing, swiping, taking screenshots, and installing apps through natural language commands.
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    MIT
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    Enables AI assistants to manage cloud infrastructure through natural language by providing a unified interface to the Dokploy platform. Supports Docker containers, applications, databases, domains, monitoring, and deployment operations through conversational commands.
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    Enables AI assistants to manage Proxmox VE virtual machines via MCP and OpenAPI, supporting operations like start, stop, clone, and snapshot.
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    MIT
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    Enables AI agents to manage and interact with Kasm Workspaces containerized desktop infrastructure, providing tools for session management, command execution, file operations, and user management via the Model Context Protocol.
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    MIT
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    MCP server for interacting with QUADS infrastructure systems via API, enabling resource management and automation through LLM applications.
    Last updated
    MIT