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predictive-maintenance-mcp

Active·★ 42·NOASSERTION·Updated 2026-05-15
★ Trending★ Workflow Automation★ Observability

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.

This open-source MCP server and Claude Code plugin turns LLMs into condition monitoring assistants. Engineers describe their needs in plain language, and the AI calls the right analysis tools to deliver results. It supports and accelerates expert decision-making while keeping data local.

#anomaly-detection#asset-management#bearing-fault-diagnosis#claude-agents#claude-ai#condition-monitoring#envelope-analysis#fastmcp
$ Install
$ pip install predictive-maintenance-mcp
↗ Visit site★ GitHub
01

Features

0152 specialized MCP endpoints (46 tools, 2 resources, 4 prompts) for comprehensive analysis
02Privacy-first: raw data never leaves the local machine
03LLM-agnostic: works with Claude, GPT, Ollama, and any MCP-compatible client
04Modular architecture: use only the tools you need and extend with custom modules
05Interactive HTML and Word report generation with fault markers and severity assessment
02

Compatibility

Windows
Windows
Verified via docs
macOS
macOS
Verified via docs
Linux
Linux
Verified via docs
03

Quick start

1
$ pip install predictive-maintenance-mcp
04

Use cases

↳Diagnose bearing faults by loading vibration signals and running spectral analysis
↳Generate professional diagnostic reports with charts and severity assessment
↳Train anomaly detection models on healthy baselines and flag outliers in new signals
05

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Related searches

predictive-maintenance-mcp AlternativesBest Observability Tools 2026Open Source Observabilitypredictive-maintenance-mcp Tutorialpredictive-maintenance-mcp Vs Competitorsanomaly-detectionasset-managementbearing-fault-diagnosis

Comments

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  • P
    Peyton JohnsonMay 20, 2026

    Used for industrial equipment monitoring automation, the fault detection accuracy is good

  • S
    Shawn MartinezMay 18, 2026

    AI-powered fault diagnosis via MCP brings predictive maintenance to conversational workflows

  • S
    Shawn JohnsonMay 11, 2026

    The maintenance intelligence integrates with existing monitoring data sources cleanly

  • F
    Finley MartinezApr 14, 2026

    Good for operations teams that want AI-assisted maintenance without custom ML pipelines

On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 42
Last commit2w ago
StatusActive
LicenseNOASSERTION
CategoryObservability
Trend (30d)
+1.6↑ 0.7%
Links
Documentation↗Discussion↗Issues↗Releases↗

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