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genpark-autonomous-ai-fleet-governance-circuit-breaker-skill

mcp
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SUMMARY

Autonomous Multi-Agent Fleet Governance & Blast-Radius Circuit Breaker. Century Milestone Master Controller! Monitors distributed agent token burn velocity, recursive subagent spawning cascades, cyclic deadlocks, and enforces system-wide ki | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550

README.md

genpark-autonomous-ai-fleet-governance-circuit-breaker-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)

Autonomous Multi-Agent Fleet Governance & Blast-Radius Circuit Breaker. Century Milestone Master Controller! Monitors distributed agent token burn velocity, recursive subagent spawning cascades, cyclic deadlocks, and enforces system-wide kill-switch containment policies with cryptographically verifiable audit tokens.

🌐 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 AutonomousAIFleetGovernanceCircuitBreaker

def main():
    controller = AutonomousAIFleetGovernanceCircuitBreaker()
    telemetry = {
        "active_agents_count": 8,
        "max_spawn_depth": 3,
        "total_tokens_per_min": 65000,
        "cost_burn_rate_usd_hour": 18.5
    }
    res = controller.evaluate_fleet_governance(telemetry)
    print("--- Century Fleet Governance Monitor ---")
    print(f"Breaker Status: {res['circuit_breaker_state']}")
    print(f"Kill Switch Active: {res['kill_switch_active']}")
    print(f"Metrics: {res['fleet_metrics']}")

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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