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gpartin/WaveGuardClient

by Various

Python SDK for WaveGuard physics-based anomaly detection API. One call. Any data.

G

MCP

gpartin/WaveGuardClient

Added 1 June 2026

#anomaly-detection #azure-migration #gpu #machine-learning #mcp-server #python #sdk

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

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.

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