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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
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    Apache 2.0
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    Governs and automates network monitoring across SolarWinds Orion and Paessler PRTG platforms with a unified MCP server, enabling querying, alert management, and governed writes with audit logging.
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    MIT
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    Provides comprehensive monitoring and observability for MCP server ecosystems with real-time health checks, performance metrics, distributed tracing, anomaly detection, and automated performance reports using OpenTelemetry and Prometheus.
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    MIT
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    Analyzes websites like a senior performance engineer and produces prioritized Core Web Vitals recommendations. Provides 16 tools for detailed performance analysis, including Lighthouse, CrUX, WordPress and Cloudflare inspections.
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    A comprehensive Model Context Protocol (MCP) server for Grafana, Prometheus, Kafka UI, and Datadog. Features a secure "Bring Your Own Key" (BYOK) architecture where credentials stay local. Provides tools for metrics querying, dashboard inspection, Kafka lag monitoring, and unified health checks.
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    MIT
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    Enables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.
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    MIT
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    Enables comprehensive analysis of AWS Lambda performance including cold start tracking, memory utilization monitoring, cost analysis, and optimization recommendations. Provides real-time metrics, comparative analysis across multiple functions, and actionable insights to improve Lambda performance and reduce costs.
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    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.
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    Apache 2.0
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    Provides Claude AI assistants with focused monitoring tools for n8n workflow execution analysis, including active workflow listing, execution history with KPIs, and detailed failure information.
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    MIT
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    Enables AI assistants to access Scout Monitoring performance and error data through Scout's API. Provides traces, errors, metrics, and insights for Rails, Django, FastAPI, Laravel and other applications to help identify and fix performance issues like N+1 queries, slow endpoints, and memory bloat.
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    MIT