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"Troubleshooting Frontend Webpage Errors" matching MCP servers:

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    Integrates Sentry error monitoring with AI-powered analysis to automatically capture frontend JavaScript errors and provide intelligent repair suggestions through multiple AI models including OpenAI, Claude, and Gemini.
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    MCP server for AI agent deployment health — gateway status, CPU/memory/swap, recent errors from journalctl/dmesg, skill registry integrity, upgrade outcomes, cron + disk usage. Each component gets HEALTHY/DEGRADED/CRITICAL classification with overall rollup.
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    8
    MIT
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    Enables LLMs to analyze network packet captures (PCAP files) from local or remote sources through a modular architecture. Supports DNS traffic analysis with structured JSON responses for network security and troubleshooting tasks.
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    MCP plugin that alerts you when AI token usage is wasteful. Fires warnings, errors, and alerts on large outputs, verbose logs, and repetitive history, auto-suppressing noise to keep your context lean.
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    MIT
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    Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.
    Last updated
    10
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    Enables AI assistants to automatically inspect and analyze application runtime log files for debugging and troubleshooting. Supports monitoring multiple log directories simultaneously with tools for listing, reading, searching, and paginating through log files.
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    8
    MIT
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    Point your coding agent at a URL and get a real-browser QA audit: broken signup/login/checkout flows, JS console errors, missing analytics, consent + security headers, mobile tap targets, and accessibility — returned as machine-verified findings graded A-F.
    Last updated
    44
    2
    Apache 2.0
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    Enables LLM agents to search and analyze Elasticsearch logs for errors, detect recurring patterns, analyze error-rate trends, and retrieve full trace context through MCP tools.
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    6
    MIT
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    Enables AI assistants to query, analyze, and resolve errors within the GlitchTip error tracking platform by providing access to issue details and stacktraces. It allows users to list unresolved issues and mark them as fixed using natural language commands.
    Last updated
    3
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    MIT
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    Enables reading and analyzing Cloudflare Workers logpush data stored in R2 buckets. Supports searching logs with filters, viewing statistics, accessing errors, and browsing logs by date and environment.
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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.
    Last updated
    13
    29
    MIT
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    Zero-config MCP server that gives AI coding assistants a real-time diagnostic snapshot of your local dev environment. Detects framework, running services, recent errors, git state, and provides a health diagnosis in one call.
    Last updated
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    1
    MIT
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    Enables read-only Linux system diagnostics and troubleshooting on local and remote RHEL-based systems via SSH, including services, processes, logs, network, and storage analysis.
    Last updated
    20
    MIT
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    Enables read-only Linux system diagnostics and troubleshooting on RHEL-based systems, including system info, services, processes, logs, network, and storage analysis. Supports both local and remote SSH execution across multiple hosts.
    Last updated
    20
    MIT