Cloudify Connector for AI agents.
7 live capabilities
Manage multi-cloud infrastructure blueprints and deployment workflows.
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Why people use Cloudify
Cloudify for Auditing Multi-Cloud Infrastructure Blueprints
With this Connector, you just ask your agent to pull the properties for a specific blueprint. It uses get_blueprint to do the heavy lifting, giving you the exact structural data you need instantly. You stop hunting for data and start making decisions.
What Vinkius changes
You get a conversational interface for your entire cloud orchestration layer.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Debugging a stalled deployment
An engineer asks the agent to check the web-app-prod deployment.
- Real-world use case 02
Auditing cloud integrations
A platform architect asks what plugins are active for AWS.
- Real-world use case 03
Verifying node hierarchy
An SRE needs to see which nodes are in the started state for a database cluster.
Complete set · 7capabilities
The complete Cloudify capability set.
These are the exact actions your AI can choose when you ask it to work with Cloudify.
01—04
4 capabilities in this set.
Part of 7 available through Cloudify.
- 01 Capability
List deployments
See the exact structural matching for your actualized runtime schemas. It's the quickest way to verify that your deployments are running as intended.
- 02 Capability
Get deployment
Get the internal structural states and precise execution topologies for a specific deployment. This reveals the underlying layout of your live infrastructure.
- 03 Capability
List nodes
See the literal limits and specific instances routing your orchestration rules. This lets you pinpoint exactly where a node sits in the hierarchy.
- 04 Capability
List plugins
See the explicit capabilities and native orchestration limits for your installed plugins. It helps you audit what your current integrations can actually do.
05—07
3 capabilities in this set.
Part of 7 available through Cloudify.
- 05 Capability
List blueprints
View all the bounded logical arrays that manage your top-level orchestration schemas. This helps you see every blueprint available in your manager at a glance.
- 06 Capability
Get blueprint
Pull the specific properties that drive your active blueprint schemas. You can use this to see the exact rules governing a specific piece of infrastructure.
- 07 Capability
List executions
Find the active cluster limits across your deployment workflow bounds. Use this to track the progress and limits of ongoing tasks.
Set up in minutes
One URL. Then ask Cloudify to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Cloudify from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Cloudify, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Cloudify for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Cloudify URL.
- Step 03
Save and start
Save the connection and enable Cloudify in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"cloudify": {
"url": "https://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Cloudify
Open Agent mode in chat and ask: "Using Cloudify, help me...". 7 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"cloudify": {
"url": "https://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Cloudify
Ask Copilot: "Using Cloudify, help me...". 7 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"cloudify": {
"url": "https://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Cloudify
Open Cascade and ask: "Using Cloudify, help me...". 7 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"cloudify": {
"url": "https://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Cloudify
Ask Cline: "Using Cloudify, help me...". 7 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add cloudify --transport http "https://edge.vinkius.com/vk_preview_YIdeRn0hAqBloQdQ3tH0JMinN2MrEDBkMrsxMQwv/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Cloudify
Ask Claude: "Using Cloudify, show me...". 7 tools are ready
Where the request belongs
Work Cloudify can move forward.
Cloud engineers who need to check multi-cloud status without opening five browser tabs. SREs trying to find why a specific workflow failed in the middle of the night. Platform architects who need to audit plugin configurations across different environments.
Cloud Engineer
Uses this to audit complex orchestration blueprints and verify deployment states using natural language.
DevOps Engineer
Monitors workflow executions and node states to quickly identify and fix failed infrastructure tasks.
Platform Architect
Audits multi-cloud integrations and plugin configurations to ensure environment consistency.
SRE
Identifies failed executions and verifies infrastructure lifecycle states during incident response.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Railway
Manage cloud deployments via Railway. list projects, inspect services, track deployments and manage variables and volumes from any AI agent.
Northflank (Developer Cloud & Orchestration)
Manage cloud infrastructure via Northflank. deploy microservices, trigger CI builds, and audit background jobs.
Scaleway
Manage Scaleway cloud infrastructure. list, create, and control virtual instances directly from your AI agent.
Fly.io
Manage Fly.io apps, machines, and infrastructure—provision resources, control machine lifecycles, and manage volumes directly from any AI agent.
Bring your own AI
Change the model, client or framework. Keep Cloudify connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Cloudify.
The practical details behind the request, access and result.
Can I use Cloudify MCP to see my multi-cloud blueprints?
Yes, you can use this Connector to list and audit all the blueprints in your Cloudify Manager. It lets your agent show you the top-level orchestration schemas you have available without you having to log into the dashboard.
How does Cloudify MCP help with deployment tracking?
It provides a direct way to see the actual runtime schemas of your deployments. You can ask your agent to pull specific execution topologies to see exactly how your infrastructure is laid out.
Can I audit my plugins with Cloudify MCP?
Yes, you can use the list_plugins capability to see all the native orchestration limits and capabilities for your installed Python abstractions across AWS, GCP, and other providers.
Can I check node states using Cloudify MCP?
Absolutely. You can ask your agent to identify specific instances and routing rules. It helps you pinpoint exactly which nodes are active or in a specific state like 'started'.
Does Cloudify MCP work with my existing Cloudify Manager?
Yes, it connects directly to your existing Cloudify Manager. You just need to provide your Manager URL and your API Token to get started.
Can I see failed workflow executions with Cloudify MCP?
Yes, you can identify active cluster limits and monitor workflow bounds. This makes it much faster to see which part of an install or heal transaction failed.
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.
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.
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.
One connection away
Give your agent a direct line to Cloudify.
Connect Cloudify once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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