"styled-components" matching MCP servers:

Enables MCP clients and AI agents to inspect a running FLECS application through its built-in REST API, including querying entities, reading components, explaining queries, and inspecting systems and performance statistics. With explicit opt-in, it also allows small reversible changes to the live ECS world.

Enables real-time monitoring of F5 Cloud service status, including 148+ service components, active incidents, and scheduled maintenance windows with intelligent caching and dual data source reliability.

A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.

Streams live React profiler data to AI agents, enabling them to analyze performance and suggest specific, actionable fixes for slow components.