Cloudify MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Cloudify through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Cloudify, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Cloudify MCP Server
Connect your Cloudify Manager to any AI agent and take full control of your multi-cloud orchestration through natural conversation.
The Vercel AI SDK gives every Cloudify tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Blueprint Management — List and audit OASIS TOSCA blueprints parsing root Cloudify manager templates
- Deployment Tracking — Retrieve exact structural matching of actualized runtime schemas and manage infrastructure states
- Workflow Executions — Monitor install, uninstall, and heal transactions to track deployment events in real-time
- Node Inspections — Resolve deeply nested infrastructure nodes and audit lifecycle properties (started, created, deleted)
- Plugin Auditing — Discover installed Python abstractions for AWS, GCP, and other cloud integrations
The Cloudify MCP Server exposes 7 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Cloudify to Vercel AI SDK via MCP
Follow these steps to integrate the Cloudify MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 7 tools from Cloudify and passes them to the LLM
Why Use Vercel AI SDK with the Cloudify MCP Server
Vercel AI SDK provides unique advantages when paired with Cloudify through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Cloudify integration everywhere
Built-in streaming UI primitives let you display Cloudify tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Cloudify + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Cloudify MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Cloudify in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Cloudify tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Cloudify capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Cloudify through natural language queries
Cloudify MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Cloudify to Vercel AI SDK via MCP:
get_blueprint
Perform structural extraction of properties driving active blueprint schemas
get_deployment
Extracts explicitly attached internal structural states pulling precise execution topologies
list_blueprints
Identify bounded logical arrays managing top-level orchestration schemas
list_deployments
Retrieve the exact structural matching verifying actualized runtime schemas
list_executions
Identify precise active cluster limits spanning deployment workflow bounds
list_nodes
Identify exact literal limits pushing specific instances routing orchestration rules
list_plugins
Extracts explicit capabilities mapping native orchestration limits
Example Prompts for Cloudify in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Cloudify immediately.
"List all blueprints in Cloudify Manager"
"Show me the execution history for deployment 'web-app-prod'"
"What nodes are currently in the 'started' state for deployment 'db-cluster'?"
Troubleshooting Cloudify MCP Server with Vercel AI SDK
Common issues when connecting Cloudify to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpCloudify + Vercel AI SDK FAQ
Common questions about integrating Cloudify MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Cloudify with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Cloudify to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.