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    A Python framework that enables secure hardware control through the Model Context Protocol, allowing AI agents and automation systems to interact with physical devices across multiple platforms.
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    Apache 2.0
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    MCP server that gives AI agents full vision and control over Android devices via ADB and scrcpy. Supports screenshots, input, apps, UI automation, shell, files, and clipboard.
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    MIT
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    About AI/ML-powered diagnostic engine for SRE Observability on Konflux and OpenShift. It uses the Model Context Protocol (MCP) and 40+ tools to analyze logs, metrics, and traces, enabling automated RCA and predictive analysis.
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    Apache 2.0
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    Provides Unix command documentation directly within Claude conversations, allowing users to retrieve help pages, man pages, and usage information without leaving the chat interface.
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    MIT
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    Enables AI agents to execute commands in a shared tmux session that is simultaneously visible to a human via a web-based terminal UI.
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    MIT
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    A secure protocol server that allows AI assistants to safely interact with Ubuntu systems through controlled file operations, command execution, package management, and system information retrieval.
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    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.
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    MIT
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    Enables MCP-compatible agents to control an Android device over the network via ADB, providing tools for shell commands, screen capture, UI inspection, file operations, and input simulation.
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    MIT
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    Enables AI services like Claude and Cursor to remotely control a Mac by executing shell commands, managing files, and running AppleScript for UI automation. Access is secured through OAuth 2.0 authentication and encrypted tunnels to protect remote interactions.
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    MIT
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    A read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.
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    MIT
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    Enables AI agents to interact with Windows operating systems through native UI automation, file navigation, application control, and system commands. Provides seamless integration between LLMs and Windows environments for tasks like clicking, typing, launching apps, and capturing desktop state.
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    MIT
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    Enables AI agents to interact with Windows operating systems by providing tools for UI automation, file navigation, application control, and system operations. Works with any LLM to perform tasks like clicking, typing, launching applications, and executing PowerShell commands through native Windows integration.
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    MIT