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"A system for information collection, organization, tracking, categorization, and output" matching MCP servers:

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    A Node.js application that provides a JSON-RPC interface to interact with CO2 sensor data, working in both simulation mode and with real Raspberry Pi Pico hardware connections.
    3
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    A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.
    28
    65
    MIT
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    MCP server for Proxmox Backup Server. Exposes datastore status, snapshot inventory, garbage collection, verify, and prune over the PBS REST API as 13 LLM-callable tools.
    17
    GPL 3.0
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    A Model Context Protocol server implementation for iOS Simulator control, providing tools for device management, app operations, permissions, system features, and certificate handling.
    29
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    20
    MIT
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    Provides a secure MCP interface to execute commands inside Docker Compose service containers, with real-time output capture and configurable timeouts.
    1
    606
    MIT
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    A Model Context Protocol server for managing cloud servers, particularly DigitalOcean droplets, allowing users to identify providers via IP addresses and perform operations like power management, status monitoring, and resource usage tracking.
    30
    1
    MIT
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    Enables comprehensive DevOps infrastructure management through tools for Jenkins, Ansible, Terraform, Kubernetes, and Docker operations. Features a sophisticated memory system for context retention and provides validation, generation, and optimization capabilities across DevOps workflows.
    1
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    A Python-based server that enables AI assistants to interact with an Unraid server through the official Unraid GraphQL API, providing read-only access to system information, Docker containers, VMs, storage, and more.
    124
    MIT
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    Enables remote Docker management over SSH via a local MCP server, providing tools to manage containers, images, Compose, and system resources.
    1
    GPL 3.0
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    Enables comprehensive benchmarking and performance monitoring of OpenShift clusters using OVN-Kubernetes networking through automated data collection, AI-powered analysis, and report generation. Provides intelligent insights into cluster performance, bottleneck detection, and optimization recommendations.