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Benchmark for Planning and Control with Large Language Model Agents: Blocksworld with Model Context Protocol
This paper introduces a new benchmark for evaluating Large Language Model (LLM) agents in planning and execution tasks within industrial automation. It uses the Blocksworld problem with five complexity categories and integrates the Model Context Protocol (MCP) as a standardized tool interface, enabling systematic comparison of diverse LLM agent architectures.