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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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    Provides read-only access to Jaeger distributed tracing data through the Model Context Protocol. Enables Claude and other MCP-capable agents to search traces, inspect spans, and analyze service dependencies directly within conversations.
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    MIT
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    An MCP server for AI-powered log analysis that enables parsing, searching, and debugging across nine log formats directly within Claude. It features automated error extraction, sensitive data scanning, and streaming support for large log files.
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    MIT
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    An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.
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    MIT
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    Provides tools for accessing Alibaba Cloud observability products including SLS (Log Service) and ARMS (Application Real-time Monitoring Service), allowing any MCP-compatible AI assistants to quickly interact with these services.
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    Enables searching and analyzing Sentry issues, events, and traces via natural language, providing tools for error investigation and distributed tracing.
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    MIT
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    Provides a suite of 33 tools for interacting with Tencent Cloud Log Service (CLS), enabling log analysis, PromQL metrics queries, and resource management. It allows AI assistants to perform CQL/SQL retrieval, manage alarm strategies, and handle data processing tasks with tiered permission controls.
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    Apache 2.0
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    Provides tools for AI assistants to manage and diagnose MWAA Airflow environments, EMR Serverless jobs, S3 files, and Confluence documentation. It features automated pipeline failure diagnosis and comprehensive log retrieval across these integrated platforms.
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    An MCP server for the Uptrace observability platform that enables querying traces, spans, logs, and metrics through natural language. It provides tools for error analysis, service discovery, and trace visualization within MCP-compatible clients.
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    Enables AI assistants to access Scout Monitoring performance and error data through Scout's API. Provides traces, errors, metrics, and insights for Rails, Django, FastAPI, Laravel and other applications to help identify and fix performance issues like N+1 queries, slow endpoints, and memory bloat.
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    MIT
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    Provides advanced, programmable access to Zabbix monitoring data and management features, enabling querying, automation, and integration of Zabbix resources.
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    MIT