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"An analytics platform for tracking and understanding website and app performance" matching MCP servers:

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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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    A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.
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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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    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.
    1
    Apache 2.0
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    Enables AI-powered analytics from Stripe, PayPal, and Google Analytics 4 (BigQuery) data sources with built-in guardrails and automated workflows for financial and web performance insights.
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    Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.
    6
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    Enables LLMs to interact with Google Analytics Admin and Data APIs to retrieve account summaries, property details, and custom metrics. It allows users to run core and real-time reports to analyze website performance and configuration via natural language.
    7
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    Apache 2.0
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    A security-first MCP server for Umami analytics (Cloud and self-hosted v3) enabling analytics, reporting, and administration with least privilege and credential-safe design.
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    MIT
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    An unofficial server that allows AI assistants to access Fathom Analytics data, enabling users to retrieve account information, site statistics, events, aggregated reports, and real-time visitor tracking.
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    MIT
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    An MCP server that integrates Google Search Console and Google Analytics 4 to provide unified SEO and web traffic analysis. It allows users to fetch search performance data, merge page metrics, and generate automated trend reports or actionable insights through tool calls.
    16
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    A FastAPI-based server that enables executing SQL queries, managing database connections, and retrieving analytics reports through MCP-integrated endpoints. It allows users to interact with database schemas, performance metrics, and access logs using structured queries.
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    Production-ready MCP server integrating Google Search Console, GA4, and PageSpeed Insights for SEO and analytics intelligence, enabling natural-language queries to Google analytics data.
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    Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.
    47
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    Apache 2.0