Vinkius
Pulumi

Pulumi MCP. Audit infra state, deployments, and outputs via chat.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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Works with every AI agent you already use

…and any MCP-compatible client

Pulumi MCP on Cursor AI Code Editor MCP Client Pulumi MCP on Claude Desktop App MCP Integration Pulumi MCP on OpenAI Agents SDK MCP Compatible Pulumi MCP on Visual Studio Code MCP Extension Client Pulumi MCP on GitHub Copilot AI Agent MCP Integration Pulumi MCP on Google Gemini AI MCP Integration Pulumi MCP on Lovable AI Development MCP Client Pulumi MCP on Mistral AI Agents MCP Compatible Pulumi MCP on Amazon AWS Bedrock MCP Support

Just plug in your AI agents and start using Vinkius.

Pulumi connects your AI agent directly to your cloud infrastructure state. It lets you list stacks, track deployment history, and audit resource outputs—all through conversation.

Check stack status (`get_stack`), review deployed IPs or URLs (`get_stack_outputs`), and manage tags for cost-center filtering without ever opening the Pulumi console.

What your AI agents can do

Create stack

Creates a new, isolated environment (stack) for your Pulumi program in the specified project.

Delete stack

Permanently removes an empty stack; this action cannot be undone.

Get current user

Returns the GitHub identity used for API calls, confirming who initiated a change.

+ 8 more capabilities included
List all infrastructure stacks

Retrieves a full inventory of your isolated project environments (dev, staging, prod) across the organization.

Manage stack state and tags

Creates new stacks or sets key-value metadata tags on existing stacks for filtering purposes.

Track deployment history

Lists all past deployments, showing the version number, status, resource changes (created/deleted), and who triggered them.

Get specific stack details

Retrieves detailed information about a single, specified Pulumi stack.

Audit deployed output values

Reads the exported configuration data (URLs, IPs) from the latest successful deployment of a stack.

Supported MCP Clients

OAuth 2.0 Compatible
Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
Vinkius runs on Zendesk Zendesk
+ other MCP clients
Included with Plan

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AI Agent

Pulumi: 11 Tools for Infra Ops

This suite of tools lets your AI agent perform full lifecycle management—from creating new environments to auditing every single deployed output value.

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 Pulumi on Vinkius
create019d8472

create stack

Creates a new, isolated environment (stack) for your Pulumi program in the specified project.

delete019d8472

delete stack

Permanently removes an empty stack; this action cannot be undone.

get019d8472

get current user

Returns the GitHub identity used for API calls, confirming who initiated a change.

get019d8472

get deployment

Retrieves detailed status information for one specific version of a deployment run.

get019d8472

get organization

Fetches high-level metadata about an entire Pulumi organization.

get019d8472

get stack

Gets the current configuration and details for a specific stack, confirming its existence and state.

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get stack outputs

Reads all exported values (like IPs or URLs) that your infrastructure program published after deployment.

list019d8472

list deployments

Lists the full history of deployments for a stack, showing status, changes, and timestamps.

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list stack tags

Retrieves all key-value metadata labels currently applied to a specific stack.

list019d8472

list stacks

Provides an inventory of every available stack in the organization, showing resource counts and last update times.

set019d8472

set stack tag

Adds or updates a custom key-value tag on a specific infrastructure stack for better filtering.

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 every call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Pulumi, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 4,800+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Every connection is secured and compliant automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Pulumi. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This server provides 11 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.

Checking cloud infrastructure state shouldn't involve opening five different tabs.

Today, checking if a stack is ready to go means jumping between the console, finding the correct project ID, clicking the deployment tab, and then manually parsing logs to see if the resource counts match what you expected. It's slow, error-prone, and takes half your morning.

With this MCP server, you simply ask: 'Is the staging stack ready?' The agent runs `get_stack` and gives you a clean status report instantly. You get authoritative state data without touching a single web console.

Pulumi MCP Server: Get infrastructure outputs with `get_stack_outputs`

Manually retrieving endpoints (like database connection strings or public URLs) means copy-pasting from the deployment page, hoping you grab the right value and that it hasn't changed since the last build.

Now, asking for `get_stack_outputs` gives you a single, clean data dump of every exported variable. It's reliable, verifiable, and ready to paste into your next script.

What you can do with this MCP connector

Your AI agent connects directly to your Pulumi infrastructure state, letting you manage cloud resources through natural language commands. You'll treat it like having a dedicated infra ops engineer sitting right next to you.

Stack Management and Organization.
You can list every isolated project environment in the organization using list_stacks, giving you an inventory of all your stacks along with their resource counts and last update times. When you need a fresh, clean sandbox for testing, use create_stack to spin up a new, dedicated stack within a specific Pulumi project.

If that test stack is empty and you're done with it, remember to call delete_stack; this action permanently wipes the environment.

**Metadata Control.**To keep your costs straight and know exactly where something belongs, you can use tags. You retrieve existing key-value labels on any specific stack using list_stack_tags. If you need to add or update a filter—say, marking it as environment=staging or team=backend—you run set_stack_tag.

Reading the State.
When you're unsure what state things are in, start with get_organization. This function pulls high-level metadata about your entire Pulumi organization. To check the specific setup of one environment, use get_stack to pull all the current configuration and details for a named stack. You can also confirm who initiated any change by calling get_current_user, which returns the GitHub identity used for every API call.

Auditing Deployments.
To track what's happened over time, you list everything using list_deployments. This shows you the full history of deployments for a stack, detailing the version number, whether it succeeded or failed, and exactly when those changes were made. To dive deep into one specific run, call get_deployment to get detailed status information for that single deployment version.

Inspecting Live Outputs.
After a successful deploy, you need to know where your stuff lives—the IPs, the URLs, the ARNs. You read all those exported values using get_stack_outputs. This tells you the live configuration data published by your infrastructure program after it successfully deployed.

Mechanics Summary.
When you're dealing with a specific stack, remember these tools: To get its current status and details, run get_stack. To see what was deployed in the past, check the list using list_deployments or focus on one version via get_deployment. If you need to filter resources by metadata, use list_stack_tags or update those filters with set_stack_tag.

You'll never have to open a console just to get these facts.

Built · Hosted · Managed by Vinkius Pulumi MCP Server - Manage Cloud State & Deployments Server ID 019d8472-4ff7-720c-8caf-a89c8ea7eb7f
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Common Questions About Pulumi MCP

How do I get a Pulumi Access Token? +

Log in to the Pulumi Console, go to Account Settings > Access Tokens, click Create Token, give it a name and copy the token immediately — it starts with pul_ and won't be shown again.

What is a Pulumi stack? +

A stack is an isolated, independently configurable instance of your Pulumi program. Stacks typically represent different environments like dev, staging and prod. Each stack has its own configuration, state, outputs and deployment history. Use list_stacks to discover all stacks in an organization.

Can I see the deployment history of a stack? +

Yes! Use list_deployments with the org name, project name and stack name. It returns the update history showing version number, status (succeeded, failed, in-progress), start/end time and resource change counts. Use get_deployment with a specific version for detailed logs and error messages.

Can I view the outputs of a stack? +

Yes! Use get_stack_outputs with the org name, project name and stack name. It returns all exported output values from the latest successful deployment, such as URLs, IP addresses, resource IDs and connection strings. This is useful for discovering endpoint addresses after infrastructure deployment.

How do I use Pulumi to set or check tags on my stacks? +

You manage organization and filtering using key-value pairs. You call set_stack_tag to add metadata like 'environment=prod' or 'cost-center=finance'. This helps your AI agent isolate specific infrastructure groups when you need to audit them.

What happens if I run the Pulumi delete_stack tool? +

This action is irreversible, so be careful. The delete_stack tool permanently removes an entire isolated instance of your code. Always confirm you need to remove all associated resources before letting your agent proceed.

How can I use Pulumi to list all my infrastructure stacks? +

Running list_stacks returns a full overview of every stack in the organization. You get details like the stack name, project, last update time, and resource count, which is great for quickly auditing your environment landscape.

How does Pulumi verify which user is running my operations? +

You use get_current_user to get the authenticated identity details. This confirms the GitHub login, name, and email address tied to the access token. It's key for auditing who actually triggered a deployment or change.

Built & Managed by Vinkius 30s setup 11 tools

We've already built the connector for Pulumi. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 11 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
+ other MCP clients

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