VictoriaMetrics Anomaly Detection MCP Server
MCP server for VictoriaMetrics anomaly detection (vmanomaly) — the ML-powered anomaly detection component for VictoriaMetrics time-series database. Enables AI agents to query anomaly scores, configure detection models, and integrate ML-based anomaly detection into operations monitoring workflows.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Infrastructure data sensitive. Enterprise auth. TLS for remote deployment.
⚡ Reliability
Best When
A VictoriaMetrics user with vmanomaly deployed wants AI agents to query anomaly detection results, configure models, and integrate ML-detected anomalies into operations workflows.
Avoid When
You use Prometheus without VictoriaMetrics, or use Datadog/Dynatrace for anomaly detection. Requires vmanomaly enterprise component.
Use Cases
- • Querying vmanomaly for detected anomalies in infrastructure metrics from SRE agents
- • Configuring anomaly detection models for specific metric patterns via DevOps agents
- • Integrating ML-based anomaly scores into AI-driven alert correlation workflows
- • Analyzing time-series anomalies across VictoriaMetrics monitored systems
Not For
- • Teams not using VictoriaMetrics (Prometheus, Datadog users need different tools)
- • Real-time streaming anomaly detection (vmanomaly processes in batch intervals)
- • Environments without vmanomaly deployed and configured
Interface
Authentication
VictoriaMetrics Enterprise features may require bearer token. Community VictoriaMetrics can have no auth or basic auth via proxy.
Pricing
VictoriaMetrics Community is free open source. vmanomaly requires Enterprise license. Community org MCP server is free open source.
Agent Metadata
Known Gotchas
- ⚠ vmanomaly requires VictoriaMetrics Enterprise license — not available in free Community edition
- ⚠ Anomaly detection models need training data period before producing useful scores
- ⚠ Community org MCP server — may lag behind VictoriaMetrics Enterprise API changes
- ⚠ VictoriaMetrics MetricsQL query language needed for accessing anomaly metric streams
Alternatives
Full Evaluation Report
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Scores are editorial opinions as of 2026-03-07.