# vmanomaly

> Use this tool when you need to detect anomalies in time series metrics using machine learning algorithms. It solves problems related to health monitoring and model management by providing 10+ detection algorithms and configuration generation. It takes time series metrics as input and outputs anomaly detection results, ideal for use cases requiring advanced monitoring and analytics, such as performance optimization and error detection.

Canonical page: https://skillsregistry.net/skills/victoriametrics-vmanomaly  
JSON: https://api.skillsregistry.net/v1/skills/victoriametrics-vmanomaly

## Description

Integrates with VictoriaMetrics' vmanomaly application for ML-based anomaly detection in time series metrics. Provides health monitoring, model management across 10+ detection algorithms (Prophet, isolation forests, Holt-Winters), configuration generation, and full-text documentation search. Requires vmanomaly v1.28.3+ with REST API access.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/victoriametrics-vmanomaly)
- **Repository:** <https://github.com/victoriametrics/mcp-vmanomaly>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "victoriametrics-vmanomaly"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/victoriametrics-vmanomaly` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/victoriametrics-vmanomaly/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt