Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@genpark-manus-autonomous-generalist-sandbox-executor-skill plan a 3-day Tokyo trip, compare flights and hotels, and draft an itinerary"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
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).
🐍 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.
Related MCP server: agentloop
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 --> Userpython example_usage.pyfrom client import ManusAutonomousSandboxExecutor
client = ManusAutonomousSandboxExecutor()
result = client.run_manus_benchmark()
print(result)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"]
}
}
}python mcp_server.py --testParameter | Type | Required | Description |
|
| Yes | Sensory inputs, task goals, or ambient telemetry |
|
| No | Cognitive depth, energy profiles, or execution timeouts |
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