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"Major Historical and Contemporary Events in Hong Kong" matching MCP servers:

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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
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    Apache 2.0
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    This server provides real-time system performance metrics via Performance Co-Pilot (PCP), enabling users to monitor CPU, memory, disk, network, processes and more through natural language queries.
    MIT
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    Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.
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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 query MQTT message history stored in SQLite, including topic inventories, last values, historical data, silent devices, and collector connection gaps. Supports publishing messages when write mode is enabled.
    8
    MIT
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    Enables AI assistants to interact with self-hosted Dynatrace Managed environments to retrieve observability data, security insights, and performance metrics. It allows users to query problems, logs, events, and SLOs through natural language interfaces in both local and remote modes.
    702
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    Apache 2.0
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    Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.
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    MIT
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    Enables real-time AI behavioral drift monitoring and detection for Claude Code, tracking shifts in model behavior across 11 major models with tools for scorecards, version changes, and compliance reports.
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    MIT
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    MCP server for tracing, logging, and debugging multi-agent systems by capturing sessions, spans, and events in a queryable trace tree.
    1
    MIT
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    Monitors development server logs in real-time and provides Claude with immediate error notifications via Server-Sent Events. Intelligently parses TypeScript, Svelte, and Vite errors with severity classification and file correlation.
    9
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    Enables real-time Kubernetes cluster observability and debugging through standardized MCP interface. Provides access to pods, services, nodes, events, and includes built-in tools for cluster health analysis and issue identification.
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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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    Enables querying and analyzing Falco security events from Falcosidekick UI through MCP tools. Supports filtering events by time windows and retrieving full event details for security monitoring and incident investigation.
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    A persistent activity log server that allows MCP-compatible AI assistants to log events, decisions, and system logs over HTTP, with a built-in web dashboard for monitoring and searching logs.
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    Read-only MCP server for searching and aggregating logs from VMware Aria Operations for Logs (formerly vRealize Log Insight). Enables querying log events, aggregating with spike detection, and retrieving alert information.
    7
    MIT
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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