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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 interaction with Sentry's error tracking and monitoring tools through a unified API, allowing natural language access to Sentry services.
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    MIT
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    An MCP server that uses SWI-Prolog for logical deduction to find root causes of errors in service dependencies, enabling root cause analysis, impact analysis, and cycle detection.
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    Creative Commons Zero v1.0 Universal
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    An enterprise-level MCP gateway and proxy that sits between an organization's MCP servers and clients. MCP Manager mitigates security threats, enables fine-grained permissions, enforces policies and guardrails, and generates comprehensive, end-to-end logs.
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    AGPL 3.0
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    Enables advanced management of Kubernetes clusters through natural language interactions. Supports querying, managing, and monitoring pods, deployments, nodes, and logs across multiple contexts and namespaces.
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    MIT
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    A middleware service that uses Model Context Protocol to analyze and automate Zabbix events with AI, enabling automated incident response and workflow automation through n8n integration.
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    An advanced system monitoring solution that uses unsupervised machine learning algorithms to detect abnormal resource usage patterns in real-time, with features including anomaly detection, process analysis, and Discord integration.
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    Session Watcher treats your prompt cache as inventory — it uses EOQ theory to tell you whether the current context is still worth carrying, and when to restart. Works with any session-based coding agent.
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    MIT
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    An MCP server for managing MCP server registries with health checks, duplicate detection, and configuration portability. It helps prevent MCP sprawl by tracking server health, identifying overlapping tools, and generating portable configurations for different clients.
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    MIT
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    A read-only MCP server for Grafana Pyroscope that lets AI assistants query continuous profiling data, including flamegraphs, hotspot functions, memory allocations, and label discovery, directly from any MCP-compatible client.
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    A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.
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    MIT
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    MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor.
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    MIT
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    Enables querying and analyzing distributed traces from Jaeger, including service discovery, trace inspection, and performance analysis, through MCP tools.
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    Apache 2.0
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    Provides access to Prometheus metrics and queries, allowing AI assistants to execute PromQL queries and analyze metrics data through standardized MCP interfaces.
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    MIT