LGDiMaggio/predictive-maintenance-mcp

AI-Powered Predictive Maintenance & Fault Diagnosis through Model Context Protocol. An open-source framework for integrating Large Language Models with predictive maintenance and fault diagnosis workflows.

47
/ 100
Emerging

This project helps operations engineers, maintenance technicians, and reliability specialists diagnose machinery health. You provide vibration data from industrial equipment, often through natural language conversations with an AI assistant like Claude. It then analyzes the data to detect issues like bearing faults, assess their severity, and generate comprehensive diagnostic reports, accelerating expert decision-making.

Used by 1 other package. Available on PyPI.

Use this if you need an AI assistant to automatically analyze vibration data, detect machinery faults, and produce detailed diagnostic reports without manual tool operation.

Not ideal if you prefer to manually operate specialized signal processing software for vibration analysis or need to perform custom, non-standard diagnostic procedures not covered by the included tools.

predictive-maintenance condition-monitoring industrial-diagnostics vibration-analysis equipment-reliability
Maintenance 10 / 25
Adoption 7 / 25
Maturity 22 / 25
Community 8 / 25

How are scores calculated?

Stars

19

Forks

2

Language

Python

License

Last pushed

Mar 11, 2026

Commits (30d)

0

Dependencies

8

Reverse dependents

1

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/mcp/LGDiMaggio/predictive-maintenance-mcp"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.