genpark-manus-autonomous-generalist-sandbox-executor-skill

mcp
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SUMMARY

General-purpose autonomous task decomposition, multi-modal web/sandbox execution loop, and self-correcting goal resolution (inspired by Manus AI).

README.md

genpark-manus-autonomous-generalist-sandbox-executor-skill

Python 3.9+
License MIT
MCP Compatible
GenPark AI
Zero Dependencies

Production-Grade Personal AI Agent Infrastructure Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)

🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation


📌 Overview & Capability

genpark-manus-autonomous-generalist-sandbox-executor-skill is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server engineered for next-generation personal AI agents (distilling breakthrough capabilities from Today AI, Manus, Cue, Meta, Muse, and Instinct).

Executive Capability: General-purpose autonomous task decomposition, multi-modal web/sandbox execution loop, and self-correcting goal resolution (inspired by Manus AI).

⚡ Key Highlights

  • 🐍 Zero External pip Dependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.
  • 🔌 Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.
  • 🧠 Personal Agent Cognitive Architecture: Fast subconscious intent reflexes, ambient screen/clipboard cues, episodic life memory, and deep autonomous task resolution.
  • 🛡️ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.

🏗️ Architecture

graph LR
    User([👤 User / Ambient Environment]) -->|Sensory Signals & Goals| Core[⚡ genpark-manus-autonomous-generalist-sandbox-executor-skill Engine]
    Core --> Memory[(🧠 Episodic & Context Graph)]
    Core --> Executor[🤖 Autonomous Action Pipeline]
    Executor --> Result[📊 Proactive Action & Telemetry]
    Result --> User

🚀 Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Programmatic Integration

from client import ManusAutonomousSandboxExecutor

client = ManusAutonomousSandboxExecutor()
result = client.run_manus_benchmark()
print(result)

🔌 Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

claude_desktop_config.json

{
  "mcpServers": {
    "genpark-manus-autonomous-generalist-sandbox-executor-skill": {
      "command": "python",
      "args": ["/path/to/genpark-manus-autonomous-generalist-sandbox-executor-skill/mcp_server.py"]
    }
  }
}

Direct MCP Testing

python mcp_server.py --test

📊 Technical Specifications

Parameter Type Required Description
payload string / dict Yes Sensory inputs, task goals, or ambient telemetry
options dict No Cognitive depth, energy profiles, or execution timeouts

Maintained with ❤️ by GenPark AI Engineering • Powering Next-Gen Personal Autonomous AI Agents 🌍

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