WEBGhosting-MCP — Cursor AI Agent
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    WEBGhosting-MCP

    WEBGhosting-MCP

    yranjan06 February 18, 2026
    26 copies 0 downloads

    Intelligent stealth browser MCP server for AI agents with 30 tools, 22 anti fingerprint scripts, and LLM powered extraction. Works seamlessly with Cursor, Claude, VS Code, and any OpenAI compatible LLM.

    <div align="center"> <img src="logo.svg" alt="WEBGhosting" width="650"> </div>

    Demo

    <div align="center"> <video src="https://github.com/user-attachments/assets/3a570664-df75-45fa-ba1e-68c5ce899061" controls width="650"></video> </div> > watch the full demo on YouTube.

    What is WEBGhosting

    The concept behind WEBGhosting is to tackle the one thing that keeps AI agents trapped in their digital boxes which is the lack of a genuine window to the world. I started with a simple question about whether an agent could navigate a complete browser just like we do, and I wanted to turn that into a reality. It is one thing to have a script that scrapes data, but it is an entirely different beast to build a system that can handle DOM perception and bypass bot detection measures while maintaining the persona of a real human. By focusing on the Model Context Protocol, I created a bridge that lets tools like Claude Code or Cursor step out of the development environment and into the live web, which is a massive leap for autonomous agents.

    The way I layered the architecture was very intentional, especially with the Go-based MCP server wrapping Playwright. Building a stealth engine with twenty-two different anti-fingerprint scripts is a level of detail that most people overlook, but it is exactly what makes the difference between a bot that gets blocked immediately and an agent that actually functions. The progression from rigid cinematic demos to a fluid voice-controlled interface highlights how much I learned about where the LLM is most effective. It was fascinating landing on that three-tier execution model because it solves the latency issues that usually kill the vibe of a voice assistant. By using regex for basic tasks and only calling the LLM for the complex stuff, I managed to make the interaction feel instantaneous.

    What I built with the Sarvam Voice Agent feels like that Jarvis moment I had been waiting for in tech. It is not just about the code or the thirt

    Tags

    ai-agentsantigravitybrowser-automationclaudecloudecopilotcursorgolangllmmcp-server

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