This is a feature-rich MCP server specifically designed for industrial predictive maintenance, offering comprehensive vibration analysis and fault diagnosis. It emphasizes privacy (local processing) and expert assistance, making it suitable for engineers seeking quick insights. Installation requires moderate technical proficiency but is well-documented. Current version targets single-machine, non-real-time scenarios.
Predictive Maintenance MCP Server is an open-source MCP server that turns LLMs into condition monitoring assistants. Engineers describe their needs in plain language, and the AI calls the right analysis tools to deliver results — bearing fault detection, risk assessment, anomaly detection, and remaining useful life estimation. It is designed to support and accelerate expert decision-making, not replace it. The server exposes 36 MCP endpoints (33 tools + 3 prompts) covering signal loading, spectral analysis, bearing fault diagnosis, ISO 20816-3 severity assessment, RAG document search, report generation (HTML/Word), and prognostics (linear, exponential, Kalman). Privacy-first: raw vibration data never leaves your machine.
setup_claude.ps1 on Windows, or manually pip install predictive-maintenance-mcp. 2. Find the full path to uvx (which uvx on macOS/Linux, where uvx on Windows). 3. Add the MCP server configuration to your client's config file (e.g., claude_desktop_config.json for Claude Desktop), using the full path to uvx. 4. Restart the client.{
"mcpServers": {
"predictive-maintenance": {
"command": "/full/path/to/uvx",
"args": ["predictive-maintenance-mcp"],
"env": { "UV_LINK_MODE": "copy" }
}
}
}