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    Minimal MCP server that integrates with Graylog, enabling agents to search, analyze, and inspect log messages across streams, discover fields and streams, and query multiple Graylog instances.
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    MIT
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    MCP server for the Chrome UX Report, providing real-user Core Web Vitals (LCP, INP, CLS) and historical trends for any origin or URL via natural language queries.
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    Enables natural language queries of the Chrome UX Report API to fetch Core Web Vitals (LCP, INP, CLS, FCP, TTFB), compare form factors, benchmark pages against site averages, and analyze up to 40 weeks of performance trends.
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    A read-only MCP server that enables AI assistants to search, aggregate, and explore OpenSearch log data through 12 tools for connectivity, index discovery, search, and aggregations.
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    An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.
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    An MCP server that gives Claude read access to Umami web analytics, allowing natural language queries for stats, breakdowns, pageview trends, live visitors, and user journeys.
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    MCP server for measuring web performance with Google PageSpeed Insights, providing median scores with uncertainty and real-user data. It offers tools for scores, diagnostics, and comparisons to identify regressions.
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    Offline MCP server with runbooks for high-volume logs, metrics, traces, and event streams. Search and diagnose symptoms without external dependencies.
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    MCP server for VibeCheck bug reports. Gives AI assistants direct access to screen recordings, console logs, network requests, user actions, and web vitals — right inside your editor.
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    MIT
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    Provides system monitoring tools for VPS including CPU, memory, disk, network ping, top processes, and Docker status, with read-only architecture and security features.
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    Privacy friendly, cookieless web analytics built MCP-first. "Add analytics to my Next.js app" → an AI agent runs the setup_analytics_for_site tool, picks the right install snippet, edits your layout file, and verifies the script is loading. OAuth onboarding, no API keys to paste.
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    Enables AI assistants to access full Datadog observability, including log search, APM trace filtering, smart sampling, and cross-correlation between logs, traces, and metrics.
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    Apache 2.0