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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.
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    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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    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.
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    MIT
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    Web-only MCP server for php-spx reports that calls embedded SPX web endpoints, parses full reports, and returns LLM-sized JSON summaries instead of raw event streams.
    7
    MIT
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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.
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    MIT
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    Enables users to ask about render performance in React and React Native apps via natural language, exposing tools for listing render hotspots and explaining component re-renders.
    MIT
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    Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.
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    A read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.
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    MIT
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    Enables AI assistants to query and analyze data in Azure Data Explorer, Log Analytics, and Microsoft Sentinel using Kusto Query Language (KQL) through tools, resources, and prompts.
    5
    MIT
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    Enables integration with Datadog APIs to monitor and retrieve information about monitors, metrics, dashboards, logs, events, and incidents through the Model Context Protocol.
    2,053
    MIT
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    Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.
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    MIT
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    Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.
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    ISC
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    An MCP server for the RocketCyber Managed SOC platform that provides read-only access to security data including incidents, agents, and events. It enables users to monitor and query security information through 10 specialized tools and resources.
    Apache 2.0
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    Mnemosyne is an MCP server that gives AI assistants deep visibility into Kubernetes clusters, enabling natural language queries about cluster state, pods, services, and more.