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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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    An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.
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    MIT
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    A FastMCP-based tool for interacting with Splunk Enterprise/Cloud through natural language. This tool provides a set of capabilities for searching Splunk data, managing KV stores, and accessing Splunk resources
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    Apache 2.0
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    A lightweight MCP server providing a single tool to interact with Dagster instances via its GraphQL API for managing runs and logs. It features minimal token overhead and optional Cloudflare Access authentication for secure deployments.
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    Model Context Protocol server for managing and diagnosing GlassFlow streaming pipelines, exposing pipeline CRUD, metrics queries, log search, and a composite diagnostic tool as MCP tools that AI agents can call over SSE transport.
    Apache 2.0
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    A live post-mortem debugger MCP server for Home Assistant that lets AI agents list captured exceptions, walk traceback frames, read local variables, and optionally evaluate Python in the context of a captured frame for true post-mortem debugging.
    MIT
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    An enterprise MCP server scaffold that provides secure, governed access to internal tools through RBAC, audit logging, rate limiting, and prompt-injection boundaries, with a FastAPI control plane and OpenTelemetry observability.
    MIT
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    Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.
    MIT
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    Enables AI assistants to interact with DataDog's observability platform through a standardized interface. Supports monitoring infrastructure, managing events, analyzing logs and metrics, and automating operations like alerts and downtimes.
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    MIT
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    SpineFrame is a audit-grade runtime that gives AI agents auditable provenance — every tool call, every piece of evidence, every decision is traced, policy-checked, and cryptographically signed. Signed evidence chains, compliance pipelines, and tool-call tracing that survives regulatory scrutiny.