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    Analyzes Microsoft Sentinel solutions from GitHub repositories to map data connectors to Log Analytics tables and query security content like detections and playbooks. It provides instant access to the official Content Hub or private repositories through a high-performance pre-built index.
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    MIT
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    Enables querying Google Analytics 4 data through MCP tools for running reports, listing properties, getting real-time metrics, and exploring metadata.
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    MIT
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    Enables exploring and diagnosing a Redis instance from MCP clients with read-only safety, using SCAN instead of KEYS for safe key enumeration.
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    An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.
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    Enables AI assistants to securely query and analyze KARTE event data via BigQuery. It provides tools for fetching event logs, aggregating data, and exploring schemas using natural language.
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    Enables querying and exploring Cribl Stream and Edge deployments, providing access to worker groups, fleets, sources, destinations, pipelines, routes, event breakers, and lookups through a structured interface.
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    MIT No Attribution
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    Enables data observability operations with the Sifflet platform. Supports exploring assets, monitors, incidents, generating monitor-as-code YAML from descriptions, and performing impact analysis.
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    AI-powered Kubernetes diagnostics that analyzes pod crashes, logs, and cluster health to provide root cause analysis and actionable solutions for common issues like CrashLoopBackOff, OOM kills, and connection errors.
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    A specialized diagnostic framework that enables AI models to self-diagnose and fix MCP-related issues by analyzing logs, validating configurations, testing connections, and implementing solutions.
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    Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.
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    Apache 2.0
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    Enables comprehensive interaction with Elasticsearch APIs through natural language queries, specifically optimized for security analysis, threat detection, incident investigation, and compliance monitoring with advanced machine learning capabilities for anomaly detection.
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    Enables querying and managing Azure Log Analytics workspaces using KQL (Kusto Query Language). Supports executing queries, managing saved queries, and exploring workspace tables and schemas with Service Principal authentication.