Formal Verification of Agentic MLOps Protocols: Model Checking and Liveness Guarantees in Distributed Model Context Protocol Workflows

Abstract

Integrating Large Language Models (LLMs) into distributed scientific workflows has established autonomous agentic tool orchestration across high-performance computing clusters. However, delegating multi-step execution graphs to generative models over unconstrained protocols exposes GPU clusters to circular wait deadlocks, resource quota starvation, and filesystem lock corruption. While the emerging Model Context Protocol (MCP) standardizes JSON-RPC tool invocation interfaces, standard deployments lack formal temporal verification guarantees. In this paper, we present a reactive formal verification framework embedded within an enterprise FastMCP tool-calling gateway governing distributed vision training pipelines. We model MCP tool interactions as a Labeled Transition System (LTS) and synthesize dynamic contractual guards enforcing three canonical Linear Temporal Logic (LTL) specifications: global deadlock freedom, bounded GPU resource reclamation, and parameterized mutual exclusion over shared CIFS storage mounts. Over 500 multi-agent scientific traces spanning execution depths up to k=14, our framework replaces exponential state explosion with a strictly linear guard progression, reducing reachable state space by over 99.66% and eliminating runtime deadlocks entirely with sub-31 ms verification overhead.