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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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    Diagnoses why a FiveM server or resource is broken by scanning local configs, manifests, and logs, returning ranked findings with evidence. It can also propose and apply low-risk text fixes when enabled.
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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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    Bridges Parallel's Monitor API with Poke to receive SMS notifications when web monitors detect changes and conversationally create/manage monitors through text messages.
    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 querying log data stored in SQLite databases through the Model Context Protocol, allowing natural language interactions with log analysis.
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    A production-oriented MCP server exposing tools for weather, currency conversion, text statistics, and server introspection, with auto-discovery, rate limiting, and API key auth.
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    Captures and stores console output from any process in SQLite with full-text search, enabling AI assistants to search logs, monitor errors, and analyze multi-process activity through natural language queries.
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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.