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Agente de automatización de navegadores

Clasificación actualizada el 30 jun 2026

For agente autónomo para automatización de navegadores, the strongest matches are executeautomation/mcp-playwright (This MCP server directly lets an LLM agent autonomously), browseros-ai/browseros (BrowserOS is an AI agent browser orchestrator and automation) and browser-use/browser-use (Browser-use is a framework purpose-built for creating autonomous AI). chromedevtools/chrome-devtools-mcp and lavague-ai/lavague round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.

Explora los mejores agentes de automatización de navegadores open-source. Compara los mejores proyectos por actividad y funcionalidades para encontrar la opción ideal para tus tareas web.

Agente de automatización de navegadores

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • executeautomation/mcp-playwrightAvatar de executeautomation

    executeautomation/mcp-playwright

    5,237Ver en GitHub↗

    This project is a Model Context Protocol server that enables Large Language Models to control Playwright browsers for web automation, scraping, and end-to-end testing. It functions as a programmable interface for executing JavaScript, capturing screenshots, and interacting with web elements across multiple browser engines. The server exposes browser automation capabilities as a set of standardized tools that models can discover and invoke. It supports session-based browser isolation to ensure unique contexts for each client connection and provides a transport layer using either standard input

    This MCP server directly lets an LLM agent autonomously drive a Playwright browser for navigation, clicking, form filling, and data extraction, with full headless support and built-in LLM integration via the Model Context Protocol.

    TypeScriptWeb ScrapingHeadless Browser ControllersBrowser Navigation
    Ver en GitHub↗5,237
  • browseros-ai/browserosAvatar de browseros-ai

    browseros-ai/BrowserOS

    9,401Ver en GitHub↗

    BrowserOS is an AI agent browser orchestrator and automation framework designed to manage browser state and execute complex web workflows. It functions as a local AI browser assistant and a Model Context Protocol controller, enabling the control of browser tabs, windows, and navigation through programmable AI agents and standardized context protocols. The system distinguishes itself through a graph-based visual workflow builder for creating repeatable automation sequences and the use of markdown-based files to define agent personalities and task recipes. It supports multi-provider orchestrati

    BrowserOS is an AI agent browser orchestrator and automation framework that directly enables LLM-driven browser control, task planning, web scraping, and headless operation, making it a comprehensive self-contained solution for building autonomous browser agents.

    C++LLM Provider IntegrationsBrowser Control ProtocolsBrowser Navigation
    Ver en GitHub↗9,401
  • browser-use/browser-useAvatar de browser-use

    browser-use/browser-use

    100,229Ver en GitHub↗

    Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web interfaces using natural language instructions. By acting as an orchestration layer between large language models and browser automation protocols, it enables the execution of complex, multi-step workflows without relying on brittle selectors. The system functions as a headless browser controller, providing a programmatic interface to manage browser instances and execute granular interactions. The project distinguishes itself through its ability to translate high-level intent into

    Browser-use is a framework purpose-built for creating autonomous AI agents that control browsers via natural language, directly covering all required features: LLM integration, browser control, headless operation, web scraping, task planning, and action extraction.

    PythonBrowser Interaction PrimitivesChrome DevTools Protocols
    Ver en GitHub↗100,229
  • chromedevtools/chrome-devtools-mcpAvatar de ChromeDevTools

    ChromeDevTools/chrome-devtools-mcp

    43,761Ver en GitHub↗

    This project serves as an agentic browser controller, providing a programmatic bridge that enables autonomous software agents to navigate web pages and interact with document elements. It functions as a browser automation protocol, facilitating headless browser operations and automated web interactions to perform repetitive tasks and end-to-end testing without manual human input. The system distinguishes itself by utilizing the Chrome DevTools Protocol to establish a bidirectional communication channel with the browser engine. This allows for protocol-based remote control, where external appl

    This project is an agentic browser controller built on the Chrome DevTools Protocol and designed for AI agents, providing programmatic browser control, headless operation, and web interaction capabilities that directly match the autonomous browsing, clicking, form-filling, and data extraction tasks you're looking for.

    TypeScriptHeadless Browsers
    Ver en GitHub↗43,761
  • lavague-ai/lavagueAvatar de lavague-ai

    lavague-ai/LaVague

    6,374Ver en GitHub↗

    LaVague is an LLM web agent framework and large action model designed to translate natural language instructions into executable browser automation scripts. It functions as a multi-modal orchestrator that reasons over web page states and HTML content to automate multi-step tasks via a Selenium-based automation engine. The framework features a modular model provider layer, allowing users to swap between different language and vision models from providers such as Anthropic, Gemini, and Azure OpenAI. It employs a multi-modal world model to process screenshots and HTML structures, utilizing retri

    LaVague is an open-source LLM-powered web agent framework that translates natural language instructions into executable browser automation scripts via Selenium, covering LLM integration, headless control, task planning, and action extraction — exactly the kind of autonomous browser control tool this search targets.

    PythonSelenium WebDriver Automations
    Ver en GitHub↗6,374
  • h4ckf0r0day/obscuraAvatar de h4ckf0r0day

    h4ckf0r0day/obscura

    16,110Ver en GitHub↗

    Obscura is a web scraping infrastructure and headless browser server designed for AI agents. It provides a system for AI models to control browser sessions, interact with websites, and extract web data using a WebSocket implementation of the Chrome DevTools Protocol. The project focuses on bot detection evasion by randomizing browser fingerprints, masking native functions, and blocking tracking scripts to mimic human behavior. It further secures identities through a traffic layer that routes network requests via HTTP or SOCKS5 proxies. The system supports large-scale data extraction through

    Obscura is a headless browser server specifically designed for AI agents to control browsers, interact with pages, and extract data via CDP, making it a direct fit for autonomous browser automation needs, though it does not include built-in LLM integration or task planning.

    RustHeadless Browser ControllersChrome DevTools ProtocolsHeadless Browser Automation
    Ver en GitHub↗16,110
  • microsoft/playwright-mcpAvatar de microsoft

    microsoft/playwright-mcp

    33,988Ver en GitHub↗

    Playwright MCP is a browser automation server that provides a standardized interface for connecting large language models to web navigation and interaction capabilities. By operating as a Model Context Protocol server, it enables external AI agents to execute browser-based tasks, extract data, and perform complex web sequences through a unified communication protocol. The project distinguishes itself by acting as a remote controller that manages headless browser lifecycles and isolated automation contexts. It maintains session-based state isolation, allowing for distinct user profiles and per

    Playwright MCP is a standardized Model Context Protocol server that connects large language models to Playwright for autonomous browser control, headless navigation, data extraction, and complex web sequences, covering exactly the LLM integration and browser automation capabilities this search requires.

    TypeScriptRemote Browser Controllers
    Ver en GitHub↗33,988
  • google-gemini/computer-use-previewAvatar de google-gemini

    google-gemini/computer-use-preview

    2,815Ver en GitHub↗

    This project is a browser automation system that connects Google's Gemini API to a web browser, enabling an AI agent to perform tasks on a user's behalf by interpreting natural language instructions. At its core, it operates through a continuous screenshot-based action loop, where the agent captures the browser's current state, sends the image to the Gemini model, and executes the model's returned commands to click, type, and navigate. The system distinguishes itself through a dual browser backend abstraction, supporting both local Playwright-controlled browsers and remote Browserbase cloud i

    This browser automation system directly connects the Gemini API to Playwright or cloud browsers, offering screenshot-driven action loops for navigation, clicking, typing, and form filling — covering LLM integration, headless mode, and action extraction in a single self-contained tool.

    PythonAI Powered Web AutomationAI-Driven Action LoopsBrowser Automation Agents
    Ver en GitHub↗2,815
  • browser-use/browser-harnessAvatar de browser-use

    browser-use/browser-harness

    15,265Ver en GitHub↗

    This project is an automation framework that connects large language models to web browsers via the Chrome DevTools Protocol for autonomous task execution. It functions as a bridge between intelligent agents and browser engines, allowing for the direct control of browser sessions and profiles. The framework features a self-healing agent capable of generating and executing custom scripts during runtime to resolve failures and optimize browser tasks. It supports stealthy deployment through the use of integrated proxies and captcha solvers to bypass bot detection and security mitigations. The s

    Browser Harness is an automation framework that connects LLMs to browsers via the Chrome DevTools Protocol for autonomous task execution, covering navigation, clicking, form filling, data extraction, headless operation, and stealth features—exactly what an AI browser automation agent needs.

    PythonChrome DevTools Protocols
    Ver en GitHub↗15,265
  • vercel-labs/agent-browserAvatar de vercel-labs

    vercel-labs/agent-browser

    36,203Ver en GitHub↗

    This project is an agentic framework designed to enable autonomous web navigation and browser automation. It functions as a controller that translates natural language instructions into deterministic browser actions, allowing agents to interact with websites, perform data extraction, and manage complex authentication flows. By leveraging accessibility trees and semantic element resolution, the framework mimics human-like navigation, moving beyond brittle DOM selectors to interact reliably with modern web interfaces. The framework distinguishes itself through its focus on secure, scalable exec

    This is a purpose-built agentic framework for autonomous web navigation that translates natural language into browser actions, covering core needs like LLM integration, task execution, and data extraction — a strong fit for your search for an AI browser automation agent.

    RustBrowser NavigationHeadless Browser Automation
    Ver en GitHub↗36,203
  • alibaba/page-agentAvatar de alibaba

    alibaba/page-agent

    19,138Ver en GitHub↗

    Page-agent is an LLM browser automation agent and JavaScript in-page GUI controller. It translates natural language instructions into direct browser interface actions to automate web-based tasks and manipulate web page elements through a programmable interface. The system coordinates complex sequences of actions across multiple browser tabs and different websites. It functions as a remote browser control server, providing an interface that allows external clients to operate a browser and manage page interactions. Its capabilities include natural language intent decoding and action mapping, D

    Page-agent is an LLM-powered browser automation agent that translates natural language into direct browser actions, coordinates multi-tab workflows, and provides a remote interface, exactly matching the search for an open-source AI agent that autonomously controls a web browser.

    TypeScriptAutonomous Browser AgentsAccessibility Tree ExtractionsBrowser Automation Agents
    Ver en GitHub↗19,138
  • browserbase/mcp-server-browserbaseAvatar de browserbase

    browserbase/mcp-server-browserbase

    3,139Ver en GitHub↗

    This project is an MCP browser automation server that connects large language models to headless cloud browsers. It functions as an autonomous web workflow engine and an LLM web agent interface, enabling the translation of natural language instructions into browser actions and structured data retrieval. The system distinguishes itself through a managed headless browser cloud API that supports concurrent Chromium sessions with integrated stealth modes, CAPTCHA solving, and proxy traffic routing. It utilizes self-healing element selection to maintain automation resilience when page structures c

    Browserbase's MCP server is an open-source tool that directly connects LLMs to headless cloud browsers for autonomous task execution, fitting the AI browser automation agent category with built-in features like stealth mode, CAPTCHA solving, and self-healing element selection.

    TypeScriptAutonomous Web AgentsHeadless Browser OrchestratorsAgentic Browser Interfaces
    Ver en GitHub↗3,139
  • browsermcp/mcpAvatar de BrowserMCP

    BrowserMCP/mcp

    5,817Ver en GitHub↗

    BrowserMCP is a browser automation bridge that connects AI tools to a live browser session through a local proxy server. It implements a standardized protocol for sending commands like click, type, and navigate to a real browser instance running on the user's machine, while keeping all browsing data on the device. The project distinguishes itself by preserving user sessions and fingerprints across automation tasks. It attaches to the user's existing browser profile to maintain cookies, logins, and authentication state, and uses the real browser's user agent, viewport, and extension context to

    BrowserMCP is a bridge that connects AI assistants directly to a live browser via the Model Context Protocol, enabling autonomous navigation, clicking, typing, and content extraction while preserving user sessions — exactly what an AI browser automation agent needs.

    TypeScriptBrowser Control ProtocolsBrowser NavigationJavaScript Execution Bridges
    Ver en GitHub↗5,817
  • agentdeskai/browser-tools-mcpAvatar de AgentDeskAI

    AgentDeskAI/browser-tools-mcp

    7,254Ver en GitHub↗

    This project is a browser automation toolset and Model Context Protocol server that connects large language models to live browser sessions. It provides a web debugging interface and a quality auditor to facilitate the analysis of document object model structures and browser logs. The system implements a bridge that streams diagnostics into AI-powered editors, allowing for the automated identification of web bugs. It features a data sanitization pipeline that removes cookies and sensitive headers to prevent private information leakage during the analysis process. The toolset covers a range o

    This repository provides a browser automation toolset and MCP (Model Context Protocol) server that connects LLMs to live browser sessions, enabling AI agents to inspect DOM structures, stream logs, and interact with pages—directly supporting the autonomous browser control and LLM integration this search targets, though focused on debugging rather than full task planning.

    JavaScriptModel Context Protocol ImplementationsAgent Context MappingsAgentic Web Interaction
    Ver en GitHub↗7,254
  • browser-act/skillsAvatar de browser-act

    browser-act/skills

    2,554Ver en GitHub↗

    This project provides an agentic web interaction engine designed to facilitate autonomous browser automation and large-scale data extraction. It serves as a framework for building and deploying agents that can navigate complex, JavaScript-rendered websites, interact with page elements, and execute multi-step workflows. By providing a structured environment for browser control, the system enables the creation of reusable automation scripts that can be deployed across diverse web platforms. The platform distinguishes itself through a comprehensive suite of security and traffic management tools,

    browser-act/skills is a CLI tool that provides browser control capabilities specifically for AI agents like Claude, enabling autonomous navigation, clicking, and data extraction with support for anti-bot bypass and multi-session operation, which directly fits the search for a tool that lets an AI agent autonomously control a web browser.

    PythonHeadless Browser Controllers
    Ver en GitHub↗2,554
Compara los 10 mejores de un vistazo
RepositorioEstrellasLenguajeLicenciaÚltimo push
executeautomation/mcp-playwright5.2KTypeScriptmit13 dic 2025
browseros-ai/browseros9.4KC++agpl-3.021 feb 2026
browser-use/browser-use100.2KPythonMIT20 jun 2026
chromedevtools/chrome-devtools-mcp43.8KTypeScriptApache-2.016 jun 2026
lavague-ai/lavague6.4KPythonApache-2.021 ene 2025
h4ckf0r0day/obscura16.1KRustApache-2.023 jun 2026
microsoft/playwright-mcp34KTypeScriptApache-2.010 jun 2026
google-gemini/computer-use-preview2.8KPythonapache-2.018 feb 2026
browser-use/browser-harness15.3KPythonMIT21 jun 2026
vercel-labs/agent-browser36.2KRustApache-2.016 jun 2026

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