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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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    A Model Context Protocol (MCP) server that exposes lnav log file analysis capabilities to AI assistants, specifically optimized for Kvaser Plain Text Log Frame CAN bus log processing.
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    MIT
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    Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.
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    Enables querying and formatting Loki logs from Grafana via the Model Context Protocol. It supports LogQL queries, label retrieval, and provides results in text, JSON, or markdown formats.
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    MIT
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    A Model Context Protocol server that analyzes various log types on Windows systems, allowing users to register, query, and analyze logs from different sources including Windows Event Logs, ETL files, and structured/unstructured text logs.
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    MIT
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    MCP server for querying VictoriaMetrics (PromQL/MetricsQL) and VictoriaLogs (LogsQL), also compatible with Prometheus, returning compact text summaries for LLM agents.
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    Enables AI models to query and analyze Kubernetes cluster logs through Grafana Loki, supporting semantic operations like error aggregation and pod restart detection. It provides tools for regex-based log searching and namespace discovery to facilitate natural language troubleshooting.