No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by LGDiMaggio · MCP Server · ★ 74
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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. It's designed to support and accelerate expert decision-making. Quick Start bash pip install p
| Stars | 74 |
| Forks | 23 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 65.2852792536938/100 |
| Open Issues | 14 |
| Last Updated | 2026-08-20 |
| Created | 2025-11-11 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~17k |
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predictive-maintenance-mcp is MCP server for predictive maintenance and machinery fault diagnosis. Gives AI assistants evidence-based vibration analysis - FFT, envelope, bearing fault detection, ISO 20816-3 severity - with a measu. It is categorized as a MCP Server with 74 GitHub stars.
predictive-maintenance-mcp is primarily written in Python. It covers topics such as ai-agent, anomaly-detection, bearing-fault-diagnosis.
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 74 stars and 23 forks, indicating an active community.
The top alternatives to predictive-maintenance-mcp on Agent Skills Hub include google-analytics-mcp, easy-mcp, PolyMCP. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.