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"Understanding Inference Models" matching MCP servers:

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    300+ MCP tools for macOS, all on-device — local AI inference (llama.cpp on Metal), voice, vision OCR, local RAG, browser automation, and ~140 system actions across 26 macOS domains. Nothing leaves your Mac.
    2
    MIT
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    A server that provides rich UI context and interaction capabilities to AI models, enabling deep understanding of user interfaces through visual analysis and precise interaction via Model Context Protocol.
    72
    MIT
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    A Model Context Protocol server that provides tools to publish messages to ROS topics via rosbridge WebSocket, enabling integration between language models and ROS-based robotics systems.
    MIT
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    MCP server that enables AI models to open the Windows Notepad application via function calling, demonstrating the complete MCP tool call workflow.
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    A stdio MCP server that provides safe local screen observation and one-step execution for desktop automation using Ollama vision models.
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    Enables AI agents to capture and analyze screenshots of macOS applications, windows, or the entire screen using local (Ollama) or cloud-based AI vision models, with non-intrusive, fast screen capture via Apple's ScreenCaptureKit.
    3
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    MIT
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    Enables LLMs to capture screenshots and screen recordings through MCP with chunked session-based transfers for reliable image consumption. Supports multi-monitor selection, timeline capture, and compatibility with both vision and non-vision language models.
    11
    1
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    Enables Large Language Models to automate macOS applications and execute AppleScript commands through natural language. It features built-in security protections including application allowlists and dangerous pattern detection to prevent unauthorized or risky system operations.
    2
    MIT
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    A TypeScript-based bridge between AI models and Android device functionality, enabling interaction with Android devices through ADB commands for tasks like app installation, file transfer, UI analysis, and shell command execution.
    10
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    MIT
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    Enables low-cost agent models to control Windows applications through a compact, state-safe proxy over Open Computer Use, reducing model-visible context by up to 99.8% with support for record/replay and reusable UI component memory.
    5
    MIT
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    A comprehensive MCP server that enables AI models to perform local file operations, command execution, and task management across multiple platforms. It features advanced capabilities like row-level file editing, directory searching, and system monitoring with built-in security filters.
    13
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    Mulan Permissive Software , Version 2
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    A secure Model Context Protocol server that allows AI models to safely interact with Windows command-line functionality, enabling controlled execution of system commands, project creation, and system information retrieval.
    8
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    MIT
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    A Model Context Protocol server that gives AI models access to your iTerm terminal session, allowing them to read output, write commands, and send control characters.
    3
    85
    MIT
  • F
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    A simple MCP server that provides accurate date and time information to Claude models, ensuring they always use the correct current date and time when creating time-sensitive content.
    3
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    A Model Context Protocol server that provides programmatic access to the Windows terminal, enabling AI models to interact with the Windows command line through standardized tools for writing commands, reading output, and sending control signals.
    3
    19
    MIT
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    Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.
    66
    310
    MIT
  • F
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    A Model Context Protocol server that enables natural language interactive control of Universal Robots collaborative robots, allowing users to control robot motion, monitor status, and execute programs through direct commands to large language models.
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