AI Agentic Commerce Telecom & Utility Bill Retention Negotiator
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
genpark-agentic-commerce-recurring-utility-bill-negotiator-skill
Official Website: https://www.genpark.ai
LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
AI Agentic Commerce Telecom & Utility Bill Retention Negotiator. Audits monthly broadband and mobile bills, detects out-of-contract price creep and hidden junk fees, and synthesizes high-leverage churn-threat retention negotiation scripts.
🌐 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: genpark-personal-agent-subscription-stealth-price-hike-detector-skill
🌟 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, andtools/call.Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
Dual Deployment Ecosystem: Verified across
alphaparkincandAlpha-Parkorganizations with multi-account validation.
🚀 Quick Start
1. Direct Python SDK Usage
from client import AgenticUtilityBillNegotiator
def main():
negotiator = AgenticUtilityBillNegotiator()
res = negotiator.audit_and_negotiate_bill("Spectrum Internet", "Ultra 500M", 89.99, contract_end_months_ago=12)
print("--- Recurring Utility Bill Audit ---")
print(f"Provider: {res['provider']} | Current: ${res['current_monthly_charge_usd']}/mo")
print(f"Target: ${res['target_benchmark_rate_usd']}/mo | Potential Savings: ${res['annual_savings_potential_usd']}/yr")
print(f"Negotiation Script:\n{res['retention_negotiation_script']}")
if __name__ == "__main__":
main()
2. Run as Model Context Protocol (MCP) Server
Start standard JSON-RPC 2.0 server over stdio:
python mcp_server.pyExecute 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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