Porter PaaS MCP. Control your entire deployment stack from chat.
Porter PaaS lets you take full command of your Kubernetes infrastructure through natural conversation. Use your AI client to map organizational projects, check cluster health, manage environments, and force rollouts—all without opening a dashboard or running complex CLI commands. It’s programmatic control over your entire deployed application stack.
Give Claude and any AI agent real-world access
Retrieves the structural metadata that defines your major organizational projects.
Inspects the core cloud credentials and definitions for an entire Kubernetes cluster.
Discovers all active applications, including those mapped to specific subdomains or custom routes.
Instructs the system to pull and deploy a specific image tag, overriding any current running container version.
Separates and lists out distinct isolation environments (like staging or pre-prod) within a single cluster.
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What AI agents can do with Porter PaaS: 10 Tools for Infrastructure Management
Use these functions to audit cluster status, deploy new versions, restart services, and map your entire application stack from a single chat interface.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Porter PaaS MCPDeploy App Tag
Forcefully updates an app's running container image to a specific version or tag, triggering a fresh deployment.
Get App
Retrieves deep metrics and resource limits for a specific deployed application.
Get Cluster
Inspects the foundational cloud credentials used by a given Kubernetes cluster.
Get Project
Pulls structural metadata related to an entire organizational project scope.
List Apps
Finds all running applications exposed under specific subdomains or custom target...
List Clusters
Lists the available cloud definitions and boundaries that host your Kubernetes nodes.
List Environments
Extracts all distinct isolation environments (like staging or pre-prod) within a cluster.
List Projects
Retrieves the unique organizational identifiers for all major projects under your...
List Helm Releases
Checks if third-party components, like databases or monitoring tools, successfully...
Restart App
Instructs the system to cycle the application's container replicas without changing...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. 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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Porter PaaS, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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The pain of the dashboard switcheroo
Today, fixing something usually means switching context five times: first to the main cloud console to check cluster status. Then into the specific application's dashboard to see logs. Next, you might open a separate terminal window just to run `kubectl` against the correct namespace. It’s clicks, tabs, and copy-pasting—a terrible way to spend an hour.
With this MCP, that entire process collapses into one chat session. You tell your agent exactly what needs doing: 'The worker is hanging.' The agent calls the necessary functions like `restart_app`, handles the cloud authentication internally, and reports back the status change in plain language. It’s just conversation.
Get instant deployment visibility with Porter PaaS.
Before this MCP, checking if a microservice was running on the correct version meant manually verifying container tags across multiple environments. You had to confirm the project ID via one tool and then check the application status in another.
Now, you ask your agent to look at the entire scope using `list_projects` and immediately get confirmation of all active apps, their associated environments, and resource mapping without ever leaving your chat window.
What Porter PaaS MCP does for your AI
Managing complex cloud deployments usually means jumping between dashboards, remembering arcane command flags, and dealing with brittle YAML files. This MCP changes that. You connect your account once to Vinkius and give your AI client deep access to your Kubernetes infrastructure. Instead of running kubectl commands or navigating resource trees, you simply ask the question.
Your agent handles the complex orchestration: listing out all organizational scopes, checking which environments are active, mapping web services, and even forcing a container mutation with a fresh image tag if something breaks.
It lets you audit an entire cluster's architecture—from high-level projects down to specific Helm charts behind your core databases. You can instruct the system to gracefully restart a hanging application pod or get precise metrics on CPU limits for a service, all from a single chat window. It’s direct control over state, not just reading logs.
019d75f8-1a9e-71db-8f74-2dc8b72e10a4 How to set up Porter PaaS MCP
The bottom line is you get programmatic control over complex cluster operations without ever leaving the chat window.
Subscribe to this MCP and provide your Porter API token.
Your AI client uses the credentials to access your cloud infrastructure data.
You interact using natural language, asking your agent to perform specific actions like listing projects or restarting pods.
Who uses Porter PaaS MCP
This MCP is for Ops Engineers who are tired of switching between dashboards and CLI tools. It’s for Backend Developers needing quick, safe ways to roll back hotfixes. And it's perfect for Engineering Leads who need instant visibility into the entire resource map.
Runs audits on cluster architectures or performs emergency restarts on services that are hanging up.
Forcing a deployment of a specific image tag to test a hotfix, or rolling back an app if the new code breaks production.
Inspecting resource mapping and isolating distinct staging environments before greenlighting a major release.
Benefits of connecting Porter PaaS MCP
Bypass dashboards and CLIs. Instead of running complex kubectl commands, you tell your agent to check the status or restart a pod, getting instant results in text form.
Safety during deployments is built-in. If an app crashes, use restart_app to cycle its replicas without having to modify the core code deployment tag first.
Full visibility across all resource types. Use list_projects and get_project to map out organizational boundaries instantly, giving you a high-level view of your infrastructure's scope.
Debugging hotfixes is fast. With deploy_app_tag, you can force an application to run a specific image tag immediately—perfect for emergency rollbacks without manual intervention.
Check everything required. You don't just see the web app; you use list_helm_releases to verify if crucial dependencies, like Postgres or Redis, actually installed correctly.
Porter PaaS MCP use cases
The weekend emergency rollback
A backend developer pushed a minor change that caused the main API to fail. They immediately use deploy_app_tag to force the application back to the stable image tag from last week, minimizing downtime and preventing manual effort.
Auditing architecture boundaries
An engineering lead needs to know how many separate testing environments exist before a major launch. They use list_environments to get an instant list of all isolated zones, confirming that the staging area is fully separated from production.
Troubleshooting a hanging worker
The queue processing service stops responding. An ops engineer uses restart_app on the specific worker app to force its pods to recycle, bringing the service back online without needing root access or SSHing into machines.
Mapping a new microservice
A team is launching a brand-new component. They use list_apps first to see what subdomains are currently active, then use get_app on the new service name to map out its exact resource requirements (CPU/RAM) before deployment.
Porter PaaS MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Manual CLI Commands
Switching between your terminal, cloud console, and dashboard tabs just to confirm if the service is running on the correct environment.
Instead of running multiple kubectl get commands, ask your agent to call list_environments, then use list_apps to see what's deployed in that specific zone. It summarizes everything for you.
Forgetting Dependencies
The main application works, but the attached database service is failing because its Helm chart didn't install correctly.
Don't assume it worked. After deployment, call list_helm_releases to verify that every dependent third-party component finished installation successfully.
Debugging without context
Getting an error message but not knowing which cluster or project the failing service belongs to.
Start by calling list_projects and then use get_project with the resulting ID. This immediately scopes the problem, helping you target the right resources.
When to use Porter PaaS MCP
Use this MCP if your primary need is deep operational control over a Kubernetes or PaaS deployment stack. You must be comfortable discussing concepts like namespaces, container tags, and resource quotas. If your job involves auditing cluster health, deploying hotfixes, or performing routine maintenance without opening a GUI, this is exactly what you want. Don't use it if you just need to retrieve simple, non-operational data; for instance, if you only needed general company metadata that isn't tied to an active cloud resource. For those cases, you might prefer a different MCP focused purely on data retrieval rather than state change.
Frequently asked questions about Porter PaaS MCP
How do I use Porter PaaS MCP to check my cluster health? +
You can inspect the core credentials of a specific K8s Cluster by calling get_cluster. This gives you visibility into the foundational cloud definitions powering your deployments.
Can I use Porter PaaS MCP to roll back an app version? +
Yes. Use the deploy_app_tag tool and provide the specific image tag or digest. This forces Kubernetes to pull that exact container version, overriding what's currently running.
What if my service is hanging? How do I fix it with Porter PaaS MCP? +
Use restart_app. This instructs the system to cycle the application's pod replicas across the cluster. It’s a non-disruptive way to clear connection leaks without changing the underlying code.
Does Porter PaaS MCP help me see all my projects? +
Absolutely. Call list_projects to retrieve all the unique organizational IDs (the projectId arrays) that define your major operational scopes within AWS or GCP clusters.
What is the difference between list_apps and list_clusters in Porter PaaS MCP? +
list_clusters gives you the boundaries of the physical cloud zones hosting your nodes. list_apps focuses on the logical layer, telling you which specific web services are running inside those clusters.