predictive-maintenance-mcp

by LGDiMaggio · MCP Server · ★ 52

About predictive-maintenance-mcp

Predictive Maintenance MCP Server Give any AI assistant the ability to analyze vibration data, detect machinery faults, and generate professional diagnostic reports — through natural conversation. An open-source MCP server and predictive maintenance AI agent that turns LLMs into condition monitoring assistants. Engineers describe what they need in plain language; the AI calls the right analysis tools and delivers results — bearing fault detection, risk assessment, anomaly detection, and remaining useful life estimation. Also available as a Claude Code plugin with 7 diagnostic skills.

anomaly-detectionasset-managementbearing-fault-diagnosisclaude-agentsclaude-aicondition-monitoringenvelope-analysisfastmcpfault-diagnosisiiot

Quick Facts

Stars52
Forks15
LanguagePython
CategoryMCP Server
Quality Score65.3670281418339/100
Open Issues1
Last Updated2026-06-29
Created2025-11-11
Platformsclaude-code, mcp, python
Est. Tokens~17k

More MCP Server Tools

Explore other popular mcp server tools:

View all MCP Server tools →

Popular Python Agent Tools

Frequently Asked Questions

What is predictive-maintenance-mcp?

predictive-maintenance-mcp is 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 workf. It is categorized as a MCP Server with 52 GitHub stars.

What programming language is predictive-maintenance-mcp written in?

predictive-maintenance-mcp is primarily written in Python. It covers topics such as anomaly-detection, asset-management, bearing-fault-diagnosis.

How do I install or use predictive-maintenance-mcp?

You can find installation instructions and usage details in the predictive-maintenance-mcp GitHub repository at github.com/LGDiMaggio/predictive-maintenance-mcp. The project has 52 stars and 15 forks, indicating an active community.

View on GitHub → Browse MCP Server tools