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93,574 servers. Updated
20 Best Browser Automation MCP Servers: compared and ranked, October 2026Ranked from 3,477 matching servers on stars, growth, downloads and maintenance. Updated .

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  • F
    license
    A
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    maintenance
    An MCP server that enables remote observation and control of a Chromium browser via a WebSocket relay, supporting DOM, CDP, and native OS automation for local or LAN-based AI agents.
    8
    -
  • A
    license
    A
    quality
    D
    maintenance
    Zero-dependency macOS desktop automation for AI agents. Screenshot, mouse, keyboard, clipboard, and window control via MCP. 18 tools, macOS 13+, one command: npx mac-use-mcp.
    18
    134 npm
    6
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    An open-source MCP server that lets any coding agent operate your computer like a person does—reading the UI through accessibility trees, clicking and typing in the background, showing an agent pointer, zooming into regions, and driving your signed-in Chrome on macOS, Windows, and Linux.
    2
    30
    8
    Apache 2.0
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    maintenance
    Enables an agent to see and operate a GNOME Wayland desktop like a human, including screenshots, mouse/keyboard control, accessibility tree access, OCR, clipboard, and audio listening.
    13
    MIT
  • A
    license
    B
    quality
    B
    maintenance
    MCP server for Windows computer use, providing low-token, low-latency automation through UIA/Win32, OCR, and vision. It enables batch actions, shortcuts, isolated desktop execution, and browser control via MCP tools.
    13
    3
    MIT
  • A
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    B
    quality
    D
    maintenance
    Exposes Anthropic's computer-use action surface (screenshot, click, move, keyboard, clipboard, batch) against a persistent desktop display via MCP stdio protocol. Enables AI agents to control a virtual desktop environment through natural language instructions.
    24
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    MCP server that enables Claude to control your computer, similar to Anthropic's computer use but easy to set up locally.
    960 npm
    379
    MIT
  • A
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    Not graded
    quality
    C
    maintenance
    Enables a constrained subagent to perform foreground GUI actions on Hyprland—observing, focusing windows, clicking, typing, scrolling, dragging, and managing the clipboard—under per-action approval with lease, audit log, and kill-switch gating.
    MIT
  • A
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    Not graded
    quality
    C
    maintenance
    Enables Claude Code to control a Windows desktop via screenshots, mouse, keyboard, and window/display enumeration, reusing the native binding from the Claude desktop app.
    MIT
  • A
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    Not graded
    quality
    D
    maintenance
    An MCP server for comprehensive browser automation and full local PC control via shell commands and Python execution. It enables tasks like web navigation, file system management, and remote access through SSE with token authentication.
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    A framework-agnostic computer-use MCP server that exposes core desktop operations (screen capture, mouse, keyboard, and file access) as standard MCP tools, enabling any MCP-compatible agent to drive a computer.
    960 npm
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Enables Windows desktop automation via MCP, allowing AI agents to control mouse, keyboard, and screen capture with the same interface as Anthropic's computer-use tool.
    4
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Standalone MCP server that gives AI agents full GUI control over macOS — screenshots, mouse, keyboard, apps, clipboard, and multi-display — with zero private dependencies.
    19
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to see, locate UI elements, and operate any Windows desktop app through natural language, using accessibility-tree matching with optional vision-model fallback, plus an autonomous visual loop with introspection and meta-learning.
    3
    MIT