DevOps engineers context-switch across Docker, Kubernetes, AWS, Terraform, and GitHub Actions a hundred times a day. MCPs collapse those into a single Claude Code session where the agent reads logs, rolls back deploys, checks cluster health, and writes the postmortem.
A DevOps / SRE / platform engineer running Kubernetes, CI/CD, observability, and on-call rotations. Lives in a terminal.
Inspect containers, tail logs, restart services, and build images — from Claude Code. Works on your local Docker, a remote host, or a CI runner.
S3, Lambda, ECS, CloudWatch — all as MCP tools. 'Show me the last 20 errors in production Lambda X' becomes a one-liner instead of a CloudWatch Insights query.
Trigger Actions, inspect workflow runs, and debug failed jobs without opening the GitHub UI. Critical for fixing CI breakages in the terminal.
Direct DB access for on-call debugging — with read-only mode by default. 'Why is user X stuck?' → Claude queries the DB, finds the row, explains the state.
Query metrics, list active alerts, and build dashboards via Claude. Especially powerful during incidents: 'show me every spike in 95p latency in the last hour'.
Auto-post incident updates, deploy announcements, and daily summaries. Claude writes the status update so you don't have to context-switch from the fix.
Triage errors, group them, assign them to the right service owner — all via Claude. Turns the Sentry inbox into a 5-minute task instead of 45.
3am PagerDuty alert: API latency spiked. You open Claude Code on your phone (via Termux). One prompt: 'investigate the latency spike'. Claude queries Grafana for the spike window, pulls the top 10 slow endpoints, checks Sentry for new errors, inspects Docker container CPU on the affected host, identifies a runaway query, lists the top Postgres statements, kills the bad query, posts an update to #incidents in Slack, and creates a Linear issue tagged @platform for tomorrow's fix. You're back in bed in 8 minutes.
DevOps engineers save 6–10h/week. Biggest wins: incident response (−50% time to mitigation), postmortem writing (−60%), cost optimization (finally actually done).
Build, tag, push to ECR and deploy to ECS in one automated pipeline triggered by a git tag or manual dispatch.
Stream Postgres metrics — query latency, lock waits, vacuum stats — into Grafana for a live operations dashboard.
Grafana alerts are enriched with runbook links and routed to the correct Slack channel based on severity and team labels.
Sentry new issues are de-duplicated, enriched with commit info, and routed to the right Slack channel based on project.
Get a Slack alert whenever a critical Supabase table row is created, updated, or deleted — ideal for audit trails.
Open a PR and a Vercel preview URL appears as a comment within minutes. Branches are cleaned up automatically when PRs close.
Scope the IAM role the AWS MCP uses — read-only for most tasks, scoped write (e.g., only Lambda updates, no IAM changes) for routine ops. Treat the MCP like a junior engineer: start read-only for a week, then widen.
The Kubernetes MCP exposes both read and write tools. Most teams keep writes gated behind a confirmation prompt or restricted to a staging cluster. For prod, use GitOps (Claude opens a PR to the manifest repo, humans merge).
Yes, via the Terraform MCP (community-maintained). `terraform plan` is safe by default. For `apply`, restrict to non-prod workspaces or require a PR-based workflow where Claude drafts the change and a human approves.
MCPs make runbooks executable. Instead of 'step 3: check CloudWatch for error rate', your runbook becomes a Claude prompt and Claude runs steps 1–10 itself. You still keep the runbook as the spec for what should happen.
PagerDuty and OpsGenie both have community MCPs. Useful for 'who's on call right now?', 'acknowledge alert X', 'escalate to secondary'. Pair with Slack MCP for incident channel coordination.
A technical founder (0–10 employees) building a B2B SaaS who ships code, handles billing, writes marketing, and answers support — all in the same day.
An indie hacker with a Twitter audience, a newsletter, 1–3 shipped products, and zero employees. Ships daily, markets constantly, avoids meetings.
A developer building AI agents, chatbots, or autonomous workflows. Needs search, scraping, vector storage, and LLM orchestration — all as tools the agent can call.
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