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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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    Local-first CLI and MCP server for turning Xcode Instruments artifacts into bounded, agent-sized evidence, with support for analyses like Time Profiler, Allocations, Network, and more.
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    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.
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    1,710
    MIT
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    An MCP server that provides AI assistants with direct access to application logs for on-demand searching, filtering, and analysis. It enables tools like Cursor to summarize log entries and identify errors within the development environment to streamline debugging.
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    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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    5
    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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    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.
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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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    Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.
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    Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.
    Last updated
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    MIT