gpartin/WaveGuardClient

Overview

A Python SDK that wraps the WaveGuard physics-based anomaly detection API. It accepts any data and returns anomaly scores with a single function call.

Best for

Best for
Developers needing a quick, physics-informed anomaly detection layer in Python

Use cases

• Detect anomalies in sensor or IoT time-series data
• Add physics-aware outlier detection to existing Python pipelines
• Prototype anomaly detection without building custom models

How to use

Install

pip install WaveGuardClient scikit-learn

Tools exposed

• waveguard_scan
• waveguard_scan_timeseries
• waveguard_health
• encoder_type

Tested with

Claude Desktop

Notes

A Python SDK that wraps the WaveGuard physics-based anomaly detection API. It accepts any data and returns anomaly scores with a single function call.

3 stars on GitHub. Last updated 2026-04-13. Licensed MIT.

Use cases

• Detect anomalies in sensor or IoT time-series data
• Add physics-aware outlier detection to existing Python pipelines
• Prototype anomaly detection without building custom models

Pros

• Simple one-call interface reduces integration effort
• Physics-based approach can catch anomalies statistical methods miss
• Works with arbitrary data formats

Cons

• Very low community adoption (3 GitHub stars) suggests limited testing
• Requires external API access, adding latency and dependency
• No documentation or examples visible beyond the repository description

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.