A browser automation tool based on the MCP architecture that combines web scraping capabilities with LLM intelligence, supports Google search, intelligent web page content extraction, and AI processing, suitable for various website types.

An MCP tool that enables Google search and web content extraction through the Chrome browser, integrated with Claude to enhance search capabilities

Fetch Browser is a powerful headless browser MCP server designed for AI agents, which can obtain web page content and perform Google searches without API keys. It supports multiple content format conversions and intelligent error handling.

This project is a Python-based multi-MCP server management framework that interacts with the Google Gemini API through the SSE protocol. It includes two major function modules: calendar management and browser automation, and supports dynamically loading multiple services through a configuration file.

An MCP server that provides Google search and web page content viewing functions, with advanced anti-bot detection evasion features, including search filtering, caching, and browser pool management.

This project implements a full-stack AI agent system inspired by the model context protocol, including a React front-end and a FastAPI back-end. The back-end serves as an AI coordinator, using Google Gemini to parse natural language instructions, safely call the file system, browser, or GitHub tools to perform tasks, and return the structured results to the front-end. The system focuses on software development scenarios, providing secure sandbox file operations, real-time web browsing, and repository inspection functions, and visualizing the tool call process.

An MCP server that provides Google search and web content viewing functions, with advanced anti-bot detection and avoidance capabilities, supporting custom search, caching, and browser instance pool management.