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genpark-agentic-subscription-churn-retention-negotiator-skill

mcp
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SUMMARY

Autonomous Subscription Churn Prediction & Dynamic Retention Negotiator. Evaluates subscriber telemetry (usage drop-off, support friction, billing price sensitivity, tenure LTV), diagnoses cancellation root cause, and dynamically negotiates | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550

README.md

genpark-agentic-subscription-churn-retention-negotiator-skill

GenPark AI
LinkedIn
License: MIT
Dependencies
MCP Compliant

Autonomous Subscription Churn Prediction & Dynamic Retention Negotiator. Evaluates subscriber telemetry (usage drop-off, support friction, billing price sensitivity, tenure LTV), diagnoses cancellation root cause, and dynamically negotiates margin-optimal save offers (subscription pause, tier right-sizing, or loyalty credit).

🌐 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

"""Example usage for AgenticSubscriptionChurnRetentionNegotiator."""
import sys
import json
from client import AgenticSubscriptionChurnRetentionNegotiator

sys.stdout.reconfigure(encoding='utf-8')

def main():
    print("=== Agentic SaaS & Commerce Subscription Churn Retention Negotiator Demo ===")
    negotiator = AgenticSubscriptionChurnRetentionNegotiator()

    sub_profile = {
        "user_id": "USR-STRIPE-8821",
        "monthly_arpu_usd": 79.00,
        "tenure_months": 10,
        "active_days_30d": 3,
        "unresolved_tickets": 0,
        "cancellation_reason": "TOO_EXPENSIVE_RIGHT_NOW"
    }

    print("\n--- 1. Evaluating Churn Probability & LTV at Risk ---")
    risk = negotiator.evaluate_churn_risk(sub_profile)
    print(f"Tier: {risk['subscriber_tier']} | LTV at Risk: ${risk['ltv_at_risk_usd']:.2f} | Churn Prob: {risk['churn_probability']*100:.0f}%")

    print("\n--- 2. Negotiating Margin-Optimal Save Counter-Offer ---")
    offer = negotiator.negotiate_retention_offer(sub_profile)
    print(f"Strategy: {offer['selected_retention_strategy']}")
    print(f"Offer Copy: '{offer['offer_headline']}'")
    print(f"Concession Cost: ${offer['concession_investment_usd']:.2f} -> Net LTV Preserved: ${offer['expected_net_ltv_preserved_usd']:.2f} (ROI: {offer['roi_multiple']}x)")

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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