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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.
    40
    1
    Apache 2.0
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    Provides Claude with read-only access to PC diagnostics including hardware specs, live performance metrics, disk usage, network checks, and more, enabling natural language queries about PC health and performance.
    15
    MIT
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    A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.
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    MIT
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    Enables LLM agents to query real-time and historical analytics from WireBoard, allowing natural language questions about visitors, events, and site metrics.
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    MIT
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    Enables AI agents to push and read metrics from EzStat, track counters/gauges, and ask natural-language questions about telemetry.
    4
    MIT
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    Connects AI assistants to Crontinel, enabling natural language queries about cron jobs, queues, Horizon status, and alerts without opening a browser.
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    MIT
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    Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.
    2
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    ISC
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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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    A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.
    1
    MIT
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    Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.
    1
    MIT
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    A Model Context Protocol server that enables retrieving and analyzing Sentry issues, including stacktraces and debugging information.
    2
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    The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.
    4
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    MIT
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    Enables interaction with Sentry's error tracking platform to fetch and manage issue details, events, and project information through the Sentry API.
    4
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    A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.
    100
    2
    MIT
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    Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.
    51
    MIT