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

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

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## 🌐 Official GenPark AI Ecosystem Links

- **GenPark Official Website**: [https://www.genpark.ai](https://www.genpark.ai)
- **LinkedIn Official Page**: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) ([https://www.llinkedin.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`, 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

```python
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`:

```bash
python mcp_server.py
```

Execute embedded test harness:

```bash
python mcp_server.py --test
```

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## 🛠️ MCP Tool Specification

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

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## 📜 License & Community

Licensed under the [MIT License](LICENSE). Copyright © 2026 [GenPark AI](https://www.genpark.ai).
Follow us on LinkedIn: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) | [https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550)