# genpark-stripe-agentic-dynamic-payment-routing-fee-optimizer-skill

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

Stripe & Mastercard Agent Connect-inspired Dynamic Payment Routing & Interchange Fee Optimizer. Evaluates transaction geography, card BIN networks, authorization probabilities, and basis-point rail costs (ACH, FedNow, Card Rails) to route payments along Pareto-optimal settlement paths.

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## 🌐 Official GenPark AI Ecosystem Links

- **GenPark Official Website**: [https://www.genpark.ai](https://www.genpark.ai)
- **LinkedIn Official Page**: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) ([https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550))

---

## 🌟 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

```python
from client import StripeAgenticDynamicPaymentRoutingOptimizer

def main():
    optimizer = StripeAgenticDynamicPaymentRoutingOptimizer()
    intent = {
        "amount_usd": 500.0,
        "currency": "USD",
        "card_network": "visa_debit",
        "country": "US"
    }
    res = optimizer.optimize_payment_route(intent)
    print("--- Stripe Dynamic Interchange Payment Routing ---")
    print(f"Optimal Rail: {res['selected_optimal_rail']['rail_name']}")
    print(f"Processing Fee: ${res['selected_optimal_rail']['processing_fee_usd']} (Effective: {res['selected_optimal_rail']['fee_effective_pct']}%)")
    print(f"Estimated Savings: ${res['savings_vs_standard_card_usd']} per transaction")

if __name__ == "__main__":
    main()

```

### 2. Run as Model Context Protocol (MCP) Server

Start standard JSON-RPC 2.0 server over `stdio`:

```bash
python mcp_server.py
```

Execute embedded test harness:

```bash
python mcp_server.py --test
```

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## 🛠️ MCP Tool Specification

Inspect [`skill.json`](skill.json) for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.

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## 📜 License & Community

Licensed under the [MIT License](LICENSE). Copyright © 2026 [GenPark AI](https://www.genpark.ai).
Follow us on LinkedIn: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) | [https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550)