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-personal-agent-dynamic-wardrobe-capsule-packer-skill Create a 5-day capsule wardrobe for San Francisco, tech conference & running, 14-22°C, 20% rain."
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.
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.
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: AI Travel Planner MCP
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.
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()
Start standard JSON-RPC 2.0 server over stdio:
python mcp_server.pyExecute embedded test harness:
python mcp_server.py --testInspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.
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
This server cannot be deployed
Your own closet in your AI: outfits from clothes you own, rendered on a model inline.
Estimate mobile-data needs and build a provider-neutral connectivity checklist for any trip.
Shared trip planner for Claude and ChatGPT: ideas, days, bookings and packing for the whole party.
Your personal AI travel concierge — flights, hotels, 116M+ POIs, visas, weather & more
