"How to manage and use Google Calendar efficiently" matching MCP servers:

MCP server that lets AI agents perform Google AI Mode searches using the user's own browser session, returning synthesized answers with citations.

Launches multiple Browser-Use agents to automatically test websites for UI bugs, broken links, accessibility issues, and other technical problems on both live and localhost sites.

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.

Let Claude Code, Codex and any AI agent use the Chrome you're already signed in to. Open-source CLI + MCP server + Chrome extension (native messaging, no debug port); stealth by default.

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.

Multi-account X (Twitter) automation that drives a real Chrome session with your own cookies, so no X API key is needed. 32 tools for posting, replies, search, engagement, and media, with draft approval on by default.

Enables AI agents to autonomously operate web browsers through the Model Context Protocol, including navigating pages, clicking, typing, filling forms, and extracting structured data.

Enables AI agents to automate both web browsers and native desktop applications through a unified interface, supporting tasks like browsing, clicking, typing, and file clipboard operations via exposed MCP tools.

An MCP server for automating browser tasks using the Browser Use API. Provides tools to run, monitor, and manage browser automation tasks.

Provides an MCP server for macOS that allows agents to control a managed browser with accessibility-first actions, visible cursor, and screenshot return.

An MCP server that connects any MCP client (like Claude or Cursor) with the browser using browser-use, allowing clients to utilize existing LLMs without requiring additional API keys.

Provides a JSON-RPC computer use runtime for macOS, exposing 7 MCP tools (observe/act/inspect/session/cancel/trace) as image content blocks so external agents like Claude Code, Pi, OpenCode, or Codex CLI can capture screenshots and drive the desktop with clicks, keys, and typing while enforcing session locking, stale-frame protection, and trace redaction server-side.

This gives Claude Desktop access to browser automation tools for web scraping, form filling, and more.

Enables any MCP-connected agent to drive a browser by reading each page as an indexed action-space table and performing one guarded operation on a numbered target, refusing and refreshing when the page changes instead of retrying selectors.

Enables coding agents to drive a real Chrome browser to complete natural-language web tasks and return evidence for verification.

A Windows-only MCP server for controlling a real browser using native screenshots, Windows accessibility, and node-interception mouse/keyboard input, without CDP or Playwright.

Enables fast, precise control of web browsers and the physical desktop through MCP, combining DOM and native OS accessibility targeting with vision-based fallback and human-like mouse movement. Supports clicking, typing, scrolling, dragging, and drawing on canvas or paint applications across Linux, Windows, and macOS.

MCP server enabling AI agents to control a real Linux browser with live view, human takeover, and safety guardrails.

Enables browser automation using Python scripts, offering operations like taking webpage screenshots, retrieving HTML content, and executing JavaScript.

AI-driven browser automation server that implements the Model Context Protocol to enable natural language control of web browsers for tasks like navigation, form filling, and visual interaction.

Facilitates browser automation with custom capabilities and agent-based interactions, integrated through the browser-use library.

Enables AI agents to control a persistent Chrome browser through a local daemon, with Jev performing routine actions and the host agent handling reasoning, text, and verification.

Provides AI clients with deterministic Playwright-driven browser control, enabling navigation, interaction, screenshots, and inspection of rendered HTML, computed styles, console diagnostics, and font audits without an embedded LLM or API key.

Pixel-level browser automation MCP server that drives a real Chrome browser using screenshots as vision input and OS-level mouse/keyboard as output, evading anti-bot detection.

Enables AI agents to operate local desktops and Chromium browsers through MCP tools, unifying accessibility trees, physical input, screenshots, DOM/ARIA, visual grounding, and result verification.

Enables browser automation through MCP clients like Claude or Cursor, using the client's existing LLM without requiring an additional API key.

Enables AI agents to control and automate browser actions through an MCP server deployed on Heroku. Supports programmatic browser automation with natural language tasks across multiple LLM providers.

Enables users to discover jobs by target titles and countries, rank job descriptions by skill coverage across all imported resumes, generate tailored ATS-ready resumes and cover letters, and fill and submit requested application batches through a signed-in AI host with browser access.

Enables MCP agents to drive the user's already-open Chrome profile through a Manifest V3 extension and loopback bridge, listing and controlling existing tabs, capturing screenshots, and sending clicks, typing, drags and key holds via an independent on-page cursor without moving the system mouse. It also supports form filling, console and network inspection, read-only or confirmed JavaScript execution, file and PDF downloads, and game-style screenshot/action loops with snapshot recovery and an emergency stop.

Enables AI agents to interact with web browsers using natural language, featuring automated browsing, form filling, vision-based element detection, and structured JSON responses for systematic browser control.