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Predictive Maintenance MCP Server: An open-source framework for integrating Large Language Models with predictive maintenance and fault diagnosis workflows

Authors: Di Maggio, Luigi Gianpio;

Predictive Maintenance MCP Server: An open-source framework for integrating Large Language Models with predictive maintenance and fault diagnosis workflows

Abstract

A Proof of Concept Model Context Protocol server demonstrating how Large Language Models like Claude can be empowered with industrial machinery diagnostics capabilities. Features real vibration data (15 bearing fault signals), FFT spectrum analysis, envelope analysis for bearing faults, ISO 20816-3 compliance checks, ML anomaly detection with semi-supervised learning, and interactive HTML reports. Demonstrates the feasibility of natural language interfaces for complex industrial diagnostics workflows.

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Keywords

industrial-iot, predictive-maintenance, fault-diagnosis, FFT-analysis, envelope-analysis, vibration-analysis, machine-learning, model-context-protocol, ISO-20816, mcp-server, claude-agents, fastmcp, iiot, asset-management, iso10816, machine-failure, condition-monitoring, claude-ai, signal-processing, predictive-analytics, industry-4-0, bearing-fault-diagnosis, industry-4.0, anomaly-detection

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    popularity
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average