genpark-manus-autonomous-web-browser-dom-actuator-skill
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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 plan | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550
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)
🌟 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, andtools/call. - Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
- Dual Deployment Ecosystem: Verified across
alphaparkincandAlpha-Parkorganizations 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
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