An astronaut overseeing a futuristic data hub
Download PDFMarkdown Version

Connect Cloudify to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Manage multi-cloud infrastructure through natural conversation.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 7 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-04

4 capabilities in this set.

Part of 7 available through Cloudify.

  1. 01

    List deployments

    This capability retrieves the exact structural matching to verify actualized runtime schemas.

  2. 02

    Get blueprint

    This capability performs structural extraction of properties that drive active blueprint schemas.

  3. 03

    List nodes

    This capability identifies exact literal limits pushing specific instances routing orchestration rules.

  4. 04

    List plugins

    Use this to extract explicit capabilities and map native orchestration limits.

Capability set02 / 02

05-07

3 capabilities in this set.

Part of 7 available through Cloudify.

  1. 05

    List blueprints

    This capability identifies bounded logical arrays managing top-level orchestration schemas.

  2. 06

    Get deployment

    This capability extracts explicitly attached internal structural states to pull precise execution topologies.

  3. 07

    List executions

    Use this to identify precise active cluster limits spanning deployment workflow bounds.

Real work

What teams actually run

01

Rapid Troubleshooting

Ask your agent to check the status of specific nodes when a deployment fails.

02

Infrastructure Auditing

Use the AI to list and verify all active blueprints and their properties.

03

Workflow Monitoring

Track the progress of install or heal transactions through your AI client.

04

Cloud Integration Checks

Verify which AWS or GCP plugins are currently active in your manager.

Automate a task

Put Cloudify to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Cloudify works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Cloudify to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

849ms average. Fast in production.

Cloudify is checked daily against the live service.

Daily averagePeak 1131ms
Oct 3Today
Fastest day
639ms
Slowest day
1131ms
14-day trend
Improving-29%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 7 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Cloudify, so you can see the experience inside your AI.

It does not authenticate your account with Cloudify. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Cloudify Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Cloudify capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "cloudify-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Cloudify in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Cloudify owners hand off.

This MCP is built for technical teams managing complex, multi-cloud environments through Cloudify.

  • 01

    Cloud Engineers

    They use the AI to manage orchestration blueprints and deployments via natural language.

  • 02

    DevOps Teams

    They monitor workflow executions and node states without opening the Cloudify UI.

  • 03

    SREs

    They use the agent to quickly identify failed executions and verify lifecycle states.

  • 04

    Platform Architects

    They audit multi-cloud integrations and plugin configurations across different environments.

FAQ

Questions Cloudify owners ask.

  • 01

    How do I connect this MCP to my Cloudify Manager?

    You need to provide your Cloudify Manager URL and your API Token during the setup process in Vinkius.

  • 02

    Which AI clients can I use with this MCP?

    You can use any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 03

    Can I monitor real-time deployment events?

    Yes, the MCP allows your agent to monitor install, uninstall, and heal transactions in real time.

  • 04

    Does this work with multi-cloud setups?

    Yes, it is designed for multi-cloud orchestration and can audit plugins for AWS, GCP, and others.

  • 05

    Do I still need to use the Cloudify Manager UI?

    While the UI remains available, this MCP allows you to perform most management and monitoring tasks through your AI agent instead.

  • 06

    Can my agent list all active cloud deployments?

    Yes. Use the 'list_deployments' capability. Your agent will retrieve the exact structural matching of your actualized runtime schemas, showing you every environment currently managed by Cloudify.

  • 07

    How do I check the lifecycle state of a specific infrastructure node?

    Provide the deployment ID to your agent and use the 'list_nodes' capability. The agent will resolve deeply nested nodes and identify whether instances are in 'started', 'created', or 'deleted' states.

  • 08

    Can I monitor pending workflow executions through the agent?

    Absolutely. The 'list_executions' capability surfaces active mapping for install, uninstall, and heal workflows. This allows you to track transactions and deployment events strictly within Cloudify limits.

Explore

More in Cloud Infrastructure

Suggestions

Connect Cloudify to Claude, Cursor, ChatGPT & more