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AI AGENTS FOR DEVOPS TOOLS (THE MCP REVOLUTION)

AI coding assistants (Claude, Cursor, Copilot) are powerful — but blind to infrastructure. They can write code but can't see your cluster state, check your Terraform plan, or query your AWS bill. You're constantly copy-pasting terminal output into chat windows.

Series: Devops (3 articles)

  1. 2
    AI AGENTS FOR DEVOPS TOOLS (THE MCP REVOLUTION) This article
Senior DevOps Engineer @VOIS | AWS Community Builder | SRE | PCSWE | CloudOps | Platform Eng.
The Model Context Protocol (MCP) solves this. It's a standard protocol that
lets AI agents call external tools natively — like giving AI eyes and hands
for infrastructure.
mcp-devops-server exposes 11 DevOps tools to any MCP-compatible AI agent:
  • kubectl get/describe/logs — "What pods are failing in production?"
  • terraform plan/show — "What will this change do?"
  • helm list/diff — "What's deployed and what's pending?"
  • docker ps/logs — "What containers are running locally?"
  • aws cost summary — "What did we spend this week?"
  • aws resource inventory — "How many EC2 instances do we have?"
The AI agent can now reason about your infrastructure directly:
You: "Why is the checkout-service returning 503s?"
Agent: [calls kubectl_get pods -n production]
Agent: [calls kubectl_logs checkout-service-7f8b9 --tail 100]
Agent: [calls kubectl_describe pod checkout-service-7f8b9]
Agent: "The checkout-service pod is in CrashLoopBackOff. The logs show an
OOM kill — the container is using 512Mi but the limit is 256Mi. The memory
limit in the deployment spec needs to be increased. Here's the patch..."
No copy-pasting. No context switching. The AI sees what you see.
This is the future: AI agents that don't just write code — they operate
infrastructure.
GitHub: https://github.com/basel5001/mcp-devops-server

Series: Devops (3 articles)

  1. 2
    AI AGENTS FOR DEVOPS TOOLS (THE MCP REVOLUTION) This article
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