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    A production-ready TypeScript template for building MCP servers with dual transport support (stdio/HTTP), OAuth 2.1 foundations, SQLite caching, observability, and security features including PII sanitization and rate limiting.
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    A server monitoring and inspection tool collection that provides remote utilities for checking network interfaces, service statuses, and firewall configurations on servers.
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    MIT
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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
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    Apache 2.0
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    The Seq MCP Server enables interaction with Seq's API endpoints for logging and monitoring, providing tools for managing signals, events, and alerts with extensive filtering and configuration options.
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    MIT
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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.
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    Apache 2.0
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    A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.
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    Apache 2.0
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    Enables managing incident response workflows including incidents, on-call, postmortems, and more through the Runframe platform using MCP tools.
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    MIT
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    Enables troubleshooting of LDAP directory services through natural language queries, providing health diagnostics, replication status, performance metrics, log analysis, and configuration comparisons across multiple servers.
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    GPL 3.0
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    An MCP server for interacting with the Rybbit Analytics API, enabling querying analytics data, managing sites, tracking events, and more.
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    MIT
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    Enables AI assistants to interact with Google Cloud Platform services for log analysis and root cause investigation. Provides tools to query Cloud Logging, detect error patterns, and perform real-time log streaming across multiple GCP projects.
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    MIT
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    Enables AI assistants to execute PromQL queries and discover metrics across multiple Prometheus tenants using the Model Context Protocol. It supports single and multi-tenant configurations with secure authentication for instant and range query analysis.
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    MIT
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    Exposes the complete Zabbix API to MCP-compatible AI assistants, enabling natural language management of hosts, problems, and templates across multiple instances. It provides 220 tools for comprehensive monitoring and configuration with support for read-only modes and secure authentication.
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    AGPL 3.0