A curated list of 218 AI tools, agents, MCP servers, and resources for DevOps, SRE, and Platform Engineering
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"awesome-devops-ai": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
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A curated list of AI tools, agents, MCP servers, and resources for DevOps, SRE, and Platform Engineering.
No automated test available for this server. Check the GitHub README for setup instructions.
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A curated list of AI tools, agents, MCP servers, and resources for DevOps, SRE, and Platform Engineering.
The AI revolution is transforming how infrastructure is built, monitored, and operated. This list tracks every meaningful tool at the intersection of AI and DevOps, from coding agents that write Terraform to AI-powered incident response that pages you with a root cause already identified.
Why this list? Engineers are adopting AI tooling faster than any technology shift in history, but the landscape is fragmented across hundreds of repos, products, and frameworks. This is one place to find them all.
459 tools across 20 categories — updated April 2026. See the Quick Start Guide for role-based recommendations.
If this list is useful, please give it a star to help others find it.
NVIDIA Grove — NVIDIA's Kubernetes API for orchestrating complex multi-node AI inference with hierarchical gang scheduling and topology-aware placement. Announced at KubeCon 2026 as part of the Dynamo ecosystem, it fills GPU orchestration gaps that plain Deployments and StatefulSets cannot cover.
Previous picks: JetBrains Junie (LLM-agnostic coding agent) | Gemini CLI (Google's terminal AI agent) | Goose (Block's Rust-based autonomous agent) | K8sGPT (CNCF Kubernetes diagnostics) | HolmesGPT (agentic troubleshooting)
May 2026