predictive-maintenance-mcp
Verified Safeby LGDiMaggio
Overview
The server provides tools for industrial machinery diagnostics, vibration analysis, bearing fault detection, and predictive maintenance workflows using time-series signal processing and machine learning, integrated with LLMs.
Installation
python src/machinery_diagnostics_server.pySecurity Notes
The server demonstrates good security practices by explicitly informing the user about critical parameter assumptions (e.g., sampling_rate, signal_unit) and requiring confirmation. It avoids `eval()` and direct network calls to external APIs, focusing on local file processing. Filename sanitization (`safe_name`) is used for reports to mitigate path traversal risks. The primary security considerations are standard for any application interacting with a local filesystem and processing user-provided documents, such as managing access permissions to data/report/model directories and exercising caution when processing untrusted PDF files due to potential PyPDF2 vulnerabilities.
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