"Element" matching MCP servers:

Enables autonomous agents to anchor browser elements from vision inputs, providing stable DOM references resilient to click drift for reliable computer-use automation.

Enables AI agents to anchor visible on-screen elements to stable DOM targets, preventing click drift during browser computer-use automation.

Enables AI agents to drive a Linux/X11 desktop via AT-SPI accessibility-tree perception and element-level actions, avoiding screenshots and coordinate clicking.

Enables AI assistants to observe, reason about, and control connected Android devices via ADB, providing tools for screenshots, UI hierarchy parsing, semantic element clicking, gestures, text input, and app lifecycle management.

Enables AI assistants to drive Kratos Multiphysics finite element simulations end to end, including introspection, scaffolding, execution, and post-processing.

A Model Context Protocol server that enables LLMs to create, modify and manipulate Excalidraw diagrams through a structured API, supporting element creation, styling, organization, and scene management.

Enables Claude to autonomously drive Firefox by combining Claude's planning with Jev's fast element selection for clicks, navigation, and form actions, reducing latency and token usage.

Enables real-time screen monitoring, UI element analysis, and predictive user behavior learning for AI assistants.

Small MCP server for GNOME Wayland desktop automation, enabling element lookup, activation, typing, screenshots, and wait helpers through AT-SPI and Mutter RemoteDesktop.

Enables MCP clients to run complete browser workflows through a single run_workflow tool, with anti-detection backends, intelligent element location, automatic retries, and session persistence.

Enhanced MCP server for full computer control: mouse, keyboard, screenshots, OCR, deep UI automation, semantic element actions, process management, filesystem watching, and accessibility-aware app launching.

Allows AI agents to control and interact with VS Code webviews by providing tools for navigation, element interaction, and state retrieval. It facilitates automated tasks like clicking elements, inputting text, and reading the DOM structure within a VS Code tab.

Enables MCP clients to observe and control Windows desktop applications by reading UIA element trees and capturing screenshots, then acting through UIA patterns or synthesized mouse and keyboard input. It runs standalone on an interactive Windows session, without requiring the original host application.

Enables Claude to directly control a persistent, real logged-in Chrome browser via 17 browser tools and 9 trading tools, with natural-language selectors, self-healing element resolution, and risk-limited trading operations.

Enables AI assistants to control Windows GUI by listing and focusing windows, capturing element snapshots via UIA/OCR/CDP, performing clicks/inputs/scrolls, verifying changes, waiting for screen updates, taking screenshots, and obtaining visual descriptions.

AI-driven smart browser automation MCP server supporting multiple AI providers. Enables natural language element selection and self-healing for robust web automation.

MCP server that enables AI agents to make autonomous Bitcoin Lightning Network payments using the L402 protocol. Agents can pay for API access, purchase resources, and complete transactions without human intervention — invoice comes in, sats go out, done.

Windows computer-use MCP server: accessibility-first element actions (UIA), UI read as diffed text trees instead of screenshots, guarded raw input, and a cross-session arbiter that yields to the human. 19 tools.

Enables MCP clients to inspect and operate native macOS apps through the Accessibility tree with safety-gated semantic actions, stale-state rejection, and outcome verification. Supports tools for app state reading, element finding, clicking, typing, form filling, window capture, and guarded workflows like menu selection and Save As.

Enables AI assistants to autonomously control Windows 11 and 10 desktops via sub-10ms screen capture, native UI Automation element inspection, and zero-lag keyboard and mouse input. Combines a visual plane with a semantic plane and stall detection so agents can operate real applications reliably without vision-only guessing.