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    Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.
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    Apache 2.0
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    A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.
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    MIT
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    Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.
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    The Unlicense
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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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    MIT
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    Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.
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    Apache 2.0
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    A read-only MCP server for Umami analytics, enabling natural language queries of website stats, traffic trends, events, sessions, and analytics reports.
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    Elastic 2.0
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    PiPeFlow passively tracks AI agent workflow states using a finite state machine, providing tools for declaring, advancing, and auditing pipelines with annotations and reports.
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    MIT
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    MCP server for Umami Analytics that provides read-only tools to query website stats, events, sessions, reports, and more, enabling natural language analytics queries.
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    MIT
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    A Python utility for adding usage tracking, analytics, and audit trails to MCP servers using SQLite-backed persistence. It enables developers to monitor tool, prompt, and resource activity and expose these statistics directly to LLM clients.
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    MIT
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    A Model Context Protocol server for Kubernetes that provides full resource coverage and advanced troubleshooting tools via HTTP chunked streaming. It enables users to manage clusters and diagnose complex issues like pod crashloops through specialized prompts and standard kubectl-like operations.
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    14,793
    MIT
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    A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.
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    MIT
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    Enables comprehensive analysis of Apache Spark event logs from S3, HTTP, or local sources, providing performance metrics, resource monitoring, shuffle analysis, and automated optimization recommendations with interactive HTML reports.
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    MIT