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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.
    9
    MIT
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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.
    8
    Apache 2.0
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    Read-only MCP server for exploring and searching OpenSearch clusters, enabling log analysis, index exploration, and query execution.
    MIT
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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.
    6
    MIT
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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.
    7
    2
    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.
    10
    7
    MIT
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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.
    8
    14
    1
    MIT
  • F
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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.