awesome-mcp-servers-devops and awesome-mcp-hardware

These two tools are **ecosystem siblings**, as both are "awesome lists" within the "mcp-registry-aggregators" category, but each curates a distinct subset of MCP servers: one focusing on DevOps and software infrastructure, and the other on hardware interaction.

Maintenance 10/25
Adoption 9/25
Maturity 13/25
Community 20/25
Maintenance 10/25
Adoption 5/25
Maturity 13/25
Community 11/25
Stars: 93
Forks: 23
Downloads:
Commits (30d): 0
Language:
License: CC0-1.0
Stars: 13
Forks: 2
Downloads:
Commits (30d): 0
Language:
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About awesome-mcp-servers-devops

WagnerAgent/awesome-mcp-servers-devops

A curated, DevOps-focused list of Model Context Protocol (MCP) servers—covering source control, IaC, Kubernetes, CI/CD, cloud, observability, security, and collaboration—with a bias toward maintained, production-ready integrations.

This list compiles production-ready integrations for DevOps professionals who want to connect AI teammates or other Model Context Protocol (MCP) clients to their existing tools. It provides a comprehensive catalog of servers that allow AI to interact with source control, infrastructure as code, CI/CD pipelines, and cloud platforms. The list helps DevOps engineers, SREs, and platform engineers find the right connectors to automate tasks, query systems, and manage operations through an AI interface.

DevOps Site Reliability Engineering Cloud Operations Infrastructure Management CI/CD

About awesome-mcp-hardware

beriberikix/awesome-mcp-hardware

Awesome list of MCP servers for interacting with hardware and the physical world.

This project helps developers connect AI applications to various hardware and physical systems, enabling AI models to interact with the real world. It takes commands from AI applications and translates them into actions for devices like embedded systems, robots, industrial IoT equipment, and oscilloscopes, providing real-time control and data exchange. Developers building AI-powered solutions for physical systems would use this to bridge the gap between AI and hardware.

embedded-systems robotics industrial-automation hardware-debugging iot-integration

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