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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.
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    Apache 2.0
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    Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.
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    MIT
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    Monitor the real-time status of 200+ popular APIs and services. Check if services like GitHub, Stripe, AWS, and Slack are experiencing outages or degraded performance directly from your AI assistant.
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    MIT
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    MCP server that filters Kubernetes warning/failure events and presents them to AI assistants for diagnostics. Enables AI to identify and troubleshoot cluster issues without consuming context on normal events.
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    MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.
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    Apache 2.0
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    Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.
    4
    MIT
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    An MCP server that decodes V8 CPU profiles into token-efficient bottleneck summaries for AI agents, enabling them to analyze CPU consumption, call trees, GC pressure, and async bottlenecks.
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    MIT
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    An MCP server for Dead Man's Snitch that enables AI assistants to manage monitoring snitches, including creating, updating, checking in, and pausing monitors for scheduled tasks and cron jobs.
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    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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    An on-call agent for data incidents, built on a bio-inspired context protocol. It triages data quality and freshness issues using DataHub, computing severity, blast radius, and ownership from the catalogue before generating prose.
    9
    Apache 2.0
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    An MCP server that provides monitoring tools for Codex agents, allowing them to create and wait on conditions using commands, log files, file events, and custom probes, replacing polling loops with event-driven blocking.
    5
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    MIT
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    Identifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.
    3
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    MIT
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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.
    5
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    MIT
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    AgentGuard47 is runtime safety infrastructure for AI agents. It adds budget caps, loop detection, retry limits, timeouts, local traces, and incident reports so agents can stop bad runs while they are happening, not just explain them afterward.
    7
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    MIT
  • A
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    An MCP server for Microsoft Defender Advanced Hunting that enables AI assistants to investigate security events using natural language by translating queries to KQL and executing them against Defender.
    2
    MIT
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    Exposes the Tenable Identity Exposure (TIE) REST API as tools for LLM clients, enabling queries on security profiles, activity timelines, AD objects, and more.
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    MIT
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    Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.
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    MIT