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

These two tools are competitors, as both aim to provide a curated list of Model Context Protocol (MCP) servers and tools, with the former having a more specific DevOps focus.

awesome-mcp-servers
41
Emerging
Maintenance 10/25
Adoption 9/25
Maturity 13/25
Community 20/25
Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 20/25
Stars: 93
Forks: 23
Downloads:
Commits (30d): 0
Language:
License: CC0-1.0
Stars: 13
Forks: 23
Downloads:
Commits (30d): 0
Language:
License: MIT
No Package No Dependents
Stale 6m 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-servers

habitoai/awesome-mcp-servers

A curated list of Model Context Protocol (MCP) servers and tools. Discover and explore various MCP implementations that enable AI models to connect with external data sources and tools.

This is a comprehensive directory for anyone building or managing AI models that need to interact with external systems and real-world data. It lists various tools and services that allow your AI, such as Claude, to connect with everything from databases and search engines to communication platforms and financial services. It's for AI developers, MLOps engineers, and anyone integrating AI into existing workflows.

AI-integration Model-deployment API-connectivity MLOps AI-development

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