genpark-manus-autonomous-web-browser-dom-actuator-skill

Official Website: https://www.genpark.ai
LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)

Manus & Adept ACT-1-inspired Autonomous Web Browser DOM Actuator. Flattens DOM trees into accessibility trees (AXTree), prunes non-interactive noise, synthesizes robust CSS/XPath locators, and compiles goal-driven multi-step automation plans with verification checks.

🌐 Official GenPark AI Ecosystem Links

• GenPark Official Website: https://www.genpark.ai

• LinkedIn Official Page: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)

Related MCP server: BugScout MCP Server

🌟 Key Features

• 100% Zero External Dependencies: Runs entirely on the Python 3.9+ standard library.

• Model Context Protocol (MCP) Standard: Native support for JSON-RPC 2.0 initialize, tools/list, and tools/call.

• Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.

• Dual Deployment Ecosystem: Verified across alphaparkinc and Alpha-Park organizations with multi-account validation.

🚀 Quick Start

1. Direct Python SDK Usage

from client import ManusAutonomousWebBrowserDOMActuator

def main():
    actuator = ManusAutonomousWebBrowserDOMActuator()
    sample_dom = [
        {"tag": "input", "id": "flight_origin", "text": "From Airport", "is_visible": True},
        {"tag": "input", "id": "flight_dest", "text": "To Destination", "is_visible": True},
        {"tag": "button", "id": "btn_find_flights", "text": "Find Flights Now", "is_visible": True}
    ]
    plan = actuator.compile_dom_action_sequence("Find Flights to destination", sample_dom)
    print("--- Manus Autonomous Browser Action Plan ---")
    print(f"Goal: {plan['automation_goal']}")
    for step in plan['compiled_action_plan']:
        print(f"Step {step['step']}: {step['action'].upper()} -> Selector: {step['target_selector']} (Label: '{step['element_label']}')")

if __name__ == "__main__":
    main()

2. Run as Model Context Protocol (MCP) Server

Start standard JSON-RPC 2.0 server over stdio:

python mcp_server.py

Execute embedded test harness:

python mcp_server.py --test

🛠️ MCP Tool Specification

Inspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.

📜 License & Community

Licensed under the MIT License. Copyright © 2026 GenPark AI. Follow us on LinkedIn: https://www.linkedin.com/company/92955550 | https://www.llinkedin.com/company/92955550