Deploy Containers to Production Using MCP.
Code pushed, images built, tags verified, deploys triggered, status reported , ship containers from commit to production in one prompt
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent reads GitHub: 3 PRs merged today. PR #201 'feat(api): add batch processing endpoint' in the backend repo.
PR #202 'fix(ui): cart total display' in the frontend repo. PR #203 'chore(infra): update nginx config' in the infra repo.
The agent checks Docker Hub for the backend image: `acme/api-server:v2.14.3` , built 12 minutes after the PR merge, image size 245MB, architecture linux/amd64.
The previous tag was `v2.14.2` at 238MB , a 7MB increase, which is reasonable for a new endpoint. For the frontend, the agent triggers a Netlify build and monitors: build started, completed in 2m 34s, deployed to production.
For the infra repo, the agent checks Docker Hub for the nginx image: `acme/nginx:v1.8.0` , built and tagged correctly. Pipeline status: 'All 3 PRs have corresponding artifacts.
Backend image: built. Frontend: deployed. Infra: tagged. Full stack deployment complete.'
MCP Server Orchestration: 3 MCP Servers, one intelligent agent
Connect GitHub, Docker Hub and Netlify MCP servers so your AI agent reads the latest merged PRs, verifies the corresponding Docker images were built and tagged, checks image metadata for vulnerabilities, triggers a Netlify deploy for the frontend layer, and reports the full deployment pipeline status. Full-stack teams shipping containerized backends with Netlify frontends get end-to-end deployment visibility. No switching between GitHub, Docker Hub and Netlify dashboards. One prompt and you know if your entire stack shipped.
Github
triggerReads merged PRs and commit hashes for deployment tracking
list_pull_requests get_repository_details get_file_contents list_repo_issues Docker Hub
actionVerifies image builds, tags and repository metadata
get_repository list_tags get_tag search_repositories Netlify
actionTriggers frontend deploys and monitors build status
trigger_build list_deploys get_deploy get_site Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own MCP
Turn any internal API into an MCP server. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Github, Docker Hub & Netlify ready in the catalog right now
- Add more from 4,700+ servers whenever you need
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added every week
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 4,700+ MCP servers and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across every tool, in one conversation. That's what this infrastructure was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across every platform.
Contextual Reasoning
Every decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your MCP servers once, and your agent handles the rest. Every time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius MCP catalog to handle these for you. You describe what you need. It does the rest.
Full-stack teams with containerized backends on Docker and frontends on Netlify who need end-to-end deployment verification
DevOps engineers who want automated Docker image validation , size checks, tag verification and architecture validation , after every merge
Small teams without CI/CD dashboards who need a single-prompt deployment status across GitHub, Docker Hub and Netlify
Engineering managers who need proof that every merged PR produced a corresponding deployment artifact
Frequently Asked Questions About This MCP Server Orchestration
Which MCP servers do I need for this workflow?
Three: GitHub, Docker Hub and Netlify. Connect all three to your AI client.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others.
Can I use Vercel instead of Netlify?
Yes. Replace the Netlify MCP server with the Vercel MCP server. The agent triggers deployments and monitors build status the same way.
Does it check for Docker image vulnerabilities?
The agent checks image metadata and size anomalies. For full vulnerability scanning, pair this with a dedicated security scanner MCP.
What if a Docker image is missing after a PR merge?
The agent flags it: 'PR #201 merged at 14:42 but no Docker Hub tag found for acme/api-server after v2.14.2.' This typically means the CI pipeline failed.
Can I use GitHub Container Registry instead of Docker Hub?
The Docker Hub MCP server is specific to Docker Hub. For GHCR, you can use the GitHub MCP to check package versions through the repository.
Extract Architecture Principles Using MCP
Code patterns formalized, universal laws derived, causal forces identified , replace ad-hoc architecture with mathematical proof
Find Codebase Duplications Using MCP Servers
Your codebase has 4 different implementations of date formatting, 3 versions of the retry logic, and 2 competing validation libraries , but nobody knows because grep only finds exact matches and these duplicates are semantic
Generate Error Postmortems Automatically via MCP
Errors captured, stack traces analyzed, root cause commits identified, postmortem docs generated , write incident reports without the pain
How MCP Servers Auto-Triage Bug Reports
New bugs detected, severity classified, sprint tickets created, team notified , triage your backlog without a standup
MCP Recipe for Code Review Time Analytics
Review bottlenecks detected, unreviewed PRs surfaced, reviewer workload balanced, team velocity measured , fix your code review process with data
MCP Recipe for Faster Incident Response
Endpoints monitored, failures detected, incidents auto-created, root cause traced to the commit , respond to outages before users tweet
MCP servers used in this workflow
GitHub
GitHub MCP Server manages repositories, tracks issues, and searches code via AI agents. Connect your GitHub account to your preferred AI client and automate core developer workflows—listing repos, getting file contents, or creating new issues—all from a natural conversation. Manage your entire software development lifecycle without leaving your chat window.
Docker Hub
Docker Hub MCP Server lets you manage all your container images directly through your AI agent. You can list repositories, search community images, check available tags, and even create or update your own repos without opening the website. It gives your agent the ability to act as a dedicated container registry assistant for full image lifecycle control.
Netlify
Netlify MCP Server manages your entire Netlify deployment lifecycle directly from any AI agent. Use this to list all active sites, trigger new builds instantly, track historical deployments, and monitor form submissions without touching the dashboard. You can query site metadata, check user profiles, and manage DNS zones—all via conversation.