home / mcp / autoprobemcp - a browser for your agent mcp server
Allow your Github Copilot Chat to navigate your frontend projects. Also compatible with Chat.fans Agents
Configuration
View docs{
"mcpServers": {
"wladastic-autoprobemcp": {
"command": "node",
"args": [
"/home/yourUserName/mcp-browser-server/build/index.js"
]
}
}
}AutoProbeMCP provides a Model Context Protocol server that lets AI assistants automate browser interactions through Playwright. It enables you to navigate pages, fill forms, take screenshots, run scripts, and analyze results in a structured, scriptable way, making web automation and testing with AI agents practical and reproducible.
Install and run the MCP server, then connect your MCP client (such as Chat.fans agents or GitHub Copilot Chat) to start automating browser tasks. You will launch a browser instance, navigate pages, interact with elements, capture screenshots, run JavaScript in the page context, and retrieve page information and console logs. The server supports multiple browsers and provides a set of tools you can call from your MCP client to perform common automation flows.
Prerequisites: you need Node.js installed on your system. You will also ensure Playwright browsers are installed for Chromium, Firefox, and WebKit.
# 1) Install dependencies
npm install
# 2) Build the server
npm run build
# 3) Install Playwright browsers (Chromium, Firefox, WebKit)
npx playwright install
# Optional: install system dependencies on Linux
sudo npx playwright install-depsTo run locally you will start the MCP server using the command shown in the configuration example. The server is designed to be driven by MCP clients, so you can wire it up in your development environment and begin issuing automation commands such as launching a browser, navigating to URLs, typing into fields, clicking elements, and taking screenshots.
Start a new browser instance for automation tasks.
Navigate the active browser page to a specified URL.
Click on a page element matching a selector.
Type text into an input field or form element.
Capture a screenshot of the current page or full page.
Extract text content from a page element.
Wait for a specific element to appear or disappear, with an optional timeout.
Execute custom JavaScript in the browser context and return results.
Retrieve browser console logs at varying levels (log, info, warn, error, debug).
AI-powered analysis of screenshots using Gemma3 models via Ollama (requires local setup).
Retrieve metadata about the current page, such as URL, title, and viewport.
Close the active browser instance to clean up resources.
Scroll the page in a direction with a specified distance and behavior.
Check whether vertical or horizontal scrolling is possible and report limits.