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Prometheus

bcfmtolgahanbybcfmtolgahan
•
3
•
Despliegue y DevOps
Ciencia de Datos y ML
Analíticas y Monitorización

Connects AI agents to Prometheus, enabling metric queries, alert analysis, and SRE operations through the Model Context Protocol.

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The Prometheus Server offers a robust Model Context Protocol (MCP) interface, empowering AI agents to seamlessly interact with Prometheus and Alertmanager. It provides a comprehensive suite of 38 specialized tools, including full Prometheus API coverage, SRE Golden Signals, intelligent analysis (anomaly detection, capacity forecasting, metric correlation), and PromQL helpers. Designed for production environments, it supports multiple transports (stdio, HTTP/SSE) and features Kubernetes-native deployment options with Helm charts and Terraform modules, ensuring reliability and scalability.

Características Principales

0138 comprehensive MCP Tools covering Prometheus API and intelligent analysis
02Advanced analysis capabilities like anomaly detection, capacity forecasting, and metric correlation
032 GitHub stars
04Built-in SRE Golden Signals for error rate, latency, throughput, and saturation
05PromQL helpers for query validation, explanation, suggestions, and optimization
06Production-ready with Kubernetes-native deployment options (Helm, Terraform, HPA, PDB)

Casos de Uso

01Programmatically managing Alertmanager silences and performing advanced metric comparisons.
02Empowering AI agents to autonomously query Prometheus metrics and analyze alerts.
03Automating SRE operations by calculating SLIs, detecting anomalies, and checking error budgets.