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genpark-personal-agent-social-relationship-crm-cadence-nudger-skill

mcp
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SUMMARY

Proactive Personal Agent Social Relationship CRM & Dunbar Cadence Nudger. Models concentric Dunbar social circles (Inner Circle 5, Close 15, Key Network 50, Active 150), tracks interaction recency and tie-strength decay across WhatsApp, WeC | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550

README.md

genpark-personal-agent-social-relationship-crm-cadence-nudger-skill

GenPark AI
LinkedIn
License: MIT
Dependencies
MCP Compliant

Proactive Personal Agent Social Relationship CRM & Dunbar Cadence Nudger. Models concentric Dunbar social circles (Inner Circle 5, Close 15, Key Network 50, Active 150), tracks interaction recency and tie-strength decay across WhatsApp, WeChat, and Email, and synthesizes personalized episodic reconnection nudges.

🌐 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 PersonalAgentSocialRelationshipCRMCadenceNudger."""
import sys
import json
from client import PersonalAgentSocialRelationshipCRMCadenceNudger

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

def main():
    print("=== Today AI / Meta Muse Social Relationship CRM Cadence Nudger Demo ===")
    nudger = PersonalAgentSocialRelationshipCRMCadenceNudger()

    network = [
        {
            "name": "Dr. Aris Thorne",
            "dunbar_tier": "CLOSE_FRIENDS_15",
            "days_since_last_contact": 38,
            "last_topic_memory": "his robotics lab paper at ICRA",
            "preferred_channel": "WhatsApp"
        },
        {
            "name": "Sophia Lin",
            "dunbar_tier": "INNER_CIRCLE_5",
            "days_since_last_contact": 3,
            "last_topic_memory": "weekend hiking trip",
            "preferred_channel": "WeChat"
        }
    ]

    print("\n--- 1. Evaluating Dunbar Circle Tie-Strength Warmth ---")
    report = nudger.evaluate_relationship_cadence(network)
    for c in report["prioritized_contacts"]:
        print(f"  {c['name']} ({c['dunbar_tier']}) -> Warmth: {c['tie_warmth_score']}/100 | Overdue: {c['is_overdue']}")

    print("\n--- 2. Synthesizing Episodic Reconnection Nudges ---")
    nudges = nudger.synthesize_reconnection_nudges(network)
    for n in nudges:
        print(f"  [{n['channel']} -> {n['recipient']}]: {n['suggested_message_draft']}")

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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