IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol

• URL: http://arxiv.org/abs/2510.01260v1
• Date: Thu, 25 Sep 2025 08:35:47 GMT
• Title: IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol
• Authors: Ningyuan Yang, Guanliang Lyu, Mingchen Ma, Yiyi Lu, Yiming Li, Zhihui Gao, Hancheng Ye, Jianyi Zhang, Tingjun Chen, Yiran Chen,
• Abstract summary: IoT-MCP is a novel framework that implements the Model Context Protocol (MCP) through edge-deployed servers.<n>This work delivers both an open-source integration framework and a standardized evaluation methodology for LLM-IoT systems.
• Score: 25.655629459993907
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The integration of Large Language Models (LLMs) with Internet-of-Things (IoT) systems faces significant challenges in hardware heterogeneity and control complexity. The Model Context Protocol (MCP) emerges as a critical enabler, providing standardized communication between LLMs and physical devices. We propose IoT-MCP, a novel framework that implements MCP through edge-deployed servers to bridge LLMs and IoT ecosystems. To support rigorous evaluation, we introduce IoT-MCP Bench, the first benchmark containing 114 Basic Tasks (e.g., ``What is the current temperature?'') and 1,140 Complex Tasks (e.g., ``I feel so hot, do you have any ideas?'') for IoT-enabled LLMs. Experimental validation across 22 sensor types and 6 microcontroller units demonstrates IoT-MCP's 100% task success rate to generate tool calls that fully meet expectations and obtain completely accurate results, 205ms average response time, and 74KB peak memory footprint. This work delivers both an open-source integration framework (https://github.com/Duke-CEI-Center/IoT-MCP-Servers) and a standardized evaluation methodology for LLM-IoT systems.

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