Is predictive-maintenance-mcp open source?

Yes, licensed under NOASSERTION.

predictive-maintenance-mcp

Active·★ 52·NOASSERTION·Updated 2026-07-13

★ Trending★ Workflow Automation★ Observability

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.

predictive-maintenance-mcp is currently grouped under Observability, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward 52 specialized MCP endpoints (46 tools, 2 resources, 4 prompts) for comprehensive analysis and Diagnose bearing faults by loading vibration signals and running spectral analysis. The listed license is NOASSERTION, which is useful when adoption constraints matter. It also shows measurable community traction with 52 GitHub stars.

#anomaly-detection#asset-management#bearing-fault-diagnosis#claude-agents#claude-ai#condition-monitoring#envelope-analysis#fastmcp

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

Why choose it

+52 specialized MCP endpoints (46 tools, 2 resources, 4 prompts) for comprehensive analysis

+Diagnose bearing faults by loading vibration signals and running spectral analysis

+Covers 3 supported environments or platforms, which is helpful for broader deployment needs.

+Ships with a public repository and a NOASSERTION license, which makes adoption and review easier.

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.

Compatibility

Windows

Verified via docs

macOS

Verified via docs

Linux

Verified via docs

Quick start

$ pip install predictive-maintenance-mcp

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

How it compares

≈predictive-maintenance-mcp sits in the Observability category, so it makes more sense to evaluate it alongside tools like worldmonitor instead of in isolation.

≈If your main need is closer to "Diagnose bearing faults by loading vibration signals and running spectral analysis", that use case is a better lens for comparison than broad feature checklists alone.

≈predictive-maintenance-mcp uses a NOASSERTION license, and community traction are both easier to judge in category context.

Alternatives

worldmonitor★ 62.5k

Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface

Features

Why choose it

Trade-offs

Compatibility

Quick start

Use cases

How it compares

Alternatives

Related searches

Comments

Features

Why choose it

Trade-offs

Compatibility

Quick start

Use cases

How it compares

Alternatives

Related searches

Comments