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AI Tools for DevOps and Infrastructure

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a-gnt3 min read

MCP servers and agents for CI/CD, monitoring, containers, and cloud infrastructure management.

DevOps Meets AI

DevOps is a perfect fit for AI tools. The work involves complex configurations, troubleshooting across systems, and lots of context-switching between tools. MCP servers bring all of that into a single conversational interface.

Container and Orchestration

Docker MCP Server

Manage containers without memorizing Docker commands:

  • "List all running containers and their resource usage"
  • "Show me the logs from the api-server container for the last hour"
  • "Build and start the docker-compose stack"
  • "Find containers that have restarted more than 3 times"
  • "Create a Dockerfile for a Node.js 20 application with multi-stage builds"

Kubernetes MCP Server

Cluster management through natural language:

  • "Show me all pods in the production namespace"
  • "Why is the auth-service pod in CrashLoopBackOff?"
  • "Scale the web deployment to 5 replicas"
  • "Show me the resource requests and limits for all deployments"
  • "Generate a HorizontalPodAutoscaler for the API deployment"

Cloud Platforms

AWS MCP Server

Manage AWS resources conversationally:

  • "List all EC2 instances and their states"
  • "Show me the CloudWatch metrics for the production RDS instance"
  • "What S3 buckets don't have versioning enabled?"
  • "Check the IAM policies for overly permissive access"

Vercel MCP Server

For teams deploying on Vercel:

  • "Show me recent deployments and their status"
  • "What environment variables are set for production?"
  • "Check build logs for the latest failed deployment"

CI/CD

GitHub Actions (via GitHub MCP)

The GitHub MCP server includes Actions support:

  • "Show me the status of the latest CI run"
  • "What workflow runs failed this week?"
  • "Generate a GitHub Actions workflow for running tests on PRs"
  • "Debug this workflow — it's failing on the deploy step"

Monitoring and Observability

Filesystem MCP Server (for logs)

Point filesystem at your log directories:

  • "Analyze the nginx access logs and show me the top error codes"
  • "Find all 500 errors in the application log from the last 24 hours"
  • "Identify the IPs making the most requests"
  • "Parse this log file and identify the slow queries"

Brave Search MCP Server (for incident response)

During incidents, quick research matters:

  • "Search for known issues with [service] version [X]"
  • "Find the documentation for this error code: [error]"
  • "What's the recommended fix for [specific infrastructure issue]?"

Infrastructure as Code

Filesystem + Memory MCP Servers

Write and manage IaC with AI assistance:

  • "Read our Terraform files and explain the infrastructure architecture"
  • "Generate a Terraform module for a VPC with public and private subnets"
  • "Update the Nginx config to add rate limiting on the API routes"
  • "Create an Ansible playbook for provisioning a new web server"

Store your infrastructure conventions in memory:

  • "We use Terraform for AWS, all state is in S3"
  • "Our naming convention is {env}-{service}-{resource}"
  • "We deploy to us-east-1 and eu-west-1"

Security

Sequential Thinking MCP Server

Security decisions require methodical analysis:

  • "Walk through the security implications of opening port 8080 to the public"
  • "Analyze our current SSL/TLS configuration for vulnerabilities"
  • "Review this IAM policy and identify privilege escalation risks"
  • "Create a security checklist for deploying a new microservice"

DevOps Workflows

Incident Response

  1. Check container/pod status (Docker/Kubernetes MCP)
  2. Read logs (Filesystem MCP)
  3. Research the error (Brave Search MCP)
  4. Identify root cause (Sequential Thinking MCP)
  5. Apply fix and verify
  6. Post-mortem documentation

Infrastructure Review

  1. Read current configs (Filesystem MCP)
  2. Analyze for issues (Sequential Thinking MCP)
  3. Research best practices (Brave Search MCP)
  4. Generate improvements
  5. Create PR with changes (GitHub MCP)

New Service Deployment

  1. Generate Dockerfile and configs (Filesystem MCP)
  2. Create CI/CD pipeline (GitHub MCP)
  3. Set up monitoring and alerting
  4. Document the service (Memory MCP)
  5. Deploy and verify

Find DevOps MCP servers on a-gnt.com — filter by the "DevOps" and "Infrastructure" categories.

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