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genpark-instacart-cart-substitution-affinity-resolver-skill

mcp
Guvenlik Denetimi
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SUMMARY

Instacart AI & Walmart Grocery-inspired Cart Substitution & Preference Affinity Resolver. Solves real-time out-of-stock product disruptions by enforcing dietary constraints (vegan, gluten-free, organic), unit price delta ceilings (+15%), an | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550

README.md

genpark-instacart-cart-substitution-affinity-resolver-skill

Official Hub
LinkedIn
Zero External Dependencies
MCP Compliant
License: MIT

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

Instacart AI & Walmart Grocery-inspired Cart Substitution & Preference Affinity Resolver. Solves real-time out-of-stock product disruptions by enforcing dietary constraints (vegan, gluten-free, organic), unit price delta ceilings (+15%), and brand affinity scoring.

🌐 Official GenPark AI Ecosystem Links

🌟 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 InstacartCartSubstitutionAffinityResolver

def main():
    resolver = InstacartCartSubstitutionAffinityResolver()
    out_of_stock = {
        "title": "Avocado Oil Mayo 12oz",
        "category": "Condiments",
        "brand": "Primal Kitchen",
        "price_usd": 8.99,
        "dietary_tags": ["keto", "gluten_free"]
    }
    candidates = [
        {"title": "Chosen Foods Avocado Oil Mayo 12oz", "category": "Condiments", "brand": "Chosen Foods", "price_usd": 9.29, "dietary_tags": ["keto", "gluten_free"]},
        {"title": "Standard Soybean Mayo 30oz", "category": "Condiments", "brand": "Hellmanns", "price_usd": 4.99, "dietary_tags": []}
    ]
    res = resolver.resolve_out_of_stock_substitution(out_of_stock, candidates, {"max_price_delta_pct": 10.0})
    print("--- Instacart Real-Time Substitution Decision ---")
    print(f"Original (OOS): {res['original_item']}")
    print(f"Verdict: {res['action_verdict']}")
    if res['chosen_substitute']:
        print(f"Auto-Replaced With: {res['chosen_substitute']['title']} (${res['chosen_substitute']['price_usd']})")

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

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