genpark-personal-agent-dynamic-wardrobe-capsule-packer-skill

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

Personal Agent Weather & Itinerary-Adaptive Capsule Wardrobe Packer. Synthesizes 7-day meteorological forecasts, destination dress codes (tech conference, gala, outdoor leisure), and airline carry-on limits to curate an interchangeable minimalist packing list.

🌐 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: PoloPan Fashion 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 PersonalAgentCapsuleWardrobePacker

def main():
    packer = PersonalAgentCapsuleWardrobePacker()
    wf = {"temp_min_c": 14.0, "temp_max_c": 22.0, "rain_probability_pct": 20.0}
    res = packer.curate_capsule_packing_list("San Francisco", 5, wf, ["AI Summit Keynote", "Running in Marina"])
    print("--- Capsule Wardrobe Travel Plan ---")
    print(f"Destination: {res['destination']} ({res['duration_days']} Days) | Temp: {res['temperature_range']}")
    print(f"Carry-on Compliant: {res['carry_on_compliant']} ({res['total_capsule_pieces']} pieces)")
    for it in res['capsule_manifest']:
        print(f"* [{it['category']}] {it['item']}")

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