How to Use the Civo (Cloud-native Kubernetes Cloud Provider API) MCP in Vercel AI SDK

Q: What's the best way to use the Civo (Cloud-native Kubernetes Cloud Provider API) MCP server with the Vercel AI SDK for cost monitoring?

Use your Vercel AI SDK client to periodically call the getcharges tool. You can then stream the results directly into a chart or graph component in your UI, giving users a live view of their Civo spending without needing to refresh the page.

Q: Does the Civo (Cloud-native Kubernetes Cloud Provider API) MCP server support streaming instance status changes with the Vercel AI SDK?

It does. When you call an action like rebootinstance, you can design your app to poll for status updates. The Vercel AI SDK makes it easy to stream these updates so your UI can show the instance transitioning from 'running' to 'rebooting' and back again.

Build UIs that manage Civo resources in real-time, streaming API results directly into your Vercel AI SDK application.

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Connect Civo (Cloud-native Kubernetes Cloud Provider API) MCP to Vercel AI SDK

Create your Vinkius account to connect Civo (Cloud-native Kubernetes Cloud Provider API) to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Civo (Cloud-native Kubernetes Cloud Provider API) with Vercel AI SDK

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Live Civo Cluster Dashboards

Stop showing loading spinners for infrastructure changes. Use the Vercel AI SDK to build a frontend that calls `create_cluster`, and then streams the new cluster's status directly into your UI as it becomes available. Your users see progress, not a frozen screen. Your dashboard can stay perpetually up-to-date. Have your app poll `list_clusters` in the background. When a user recycles a node with `recycle_cluster_node`, the status change appears on their screen instantly, without a page refresh. That's how you build a modern cloud control panel.

Interactive Instance Management

Let your users manage their Civo compute instances directly from your app. Your agent can call `reboot_instance` or `stop_instance`, and the Vercel AI SDK will stream the status updates. The UI can reflect the change from 'running' to 'stopping' to 'stopped' in real time. This isn't just for stopping and starting. You can build a full instance control panel. Give users buttons that trigger `resize_instance` for upgrades or `retag_instance` for better organization. The feedback is immediate, making your app feel responsive and powerful.

Stream Civo Usage with this MCP Server

Build a real-time billing dashboard for Civo services. Your AI client can call `get_charges` and stream the data straight into a chart or table in your React or Svelte app. Users see their hourly costs tick up live. It's also great for proactive alerts. Your app can monitor `get_quota` and display a warning bar in the UI when instance or volume limits are approaching. This MCP Server gives your frontend direct visibility into account status.

Setup guide

Set up Civo (Cloud-native Kubernetes Cloud Provider API) MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Civo (Cloud-native Kubernetes Cloud Provider API) tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Civo (Cloud-native Kubernetes Cloud Provider API) transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

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Common questions about Civo (Cloud-native Kubernetes Cloud Provider API) MCP in Vercel AI SDK

Connect the MCP Server to your Vercel AI SDK client and call tools like `list_clusters` or `list_instances`. The SDK's streaming capabilities will push the data directly into your UI components as it arrives, creating a live-updating dashboard.

Yes. Your Next.js application, using the Vercel AI SDK, can call tools like `create_cluster`, `list_clusters`, and `recycle_cluster_node`. This lets you build full-featured Kubernetes management interfaces directly into your product.

Use your Vercel AI SDK client to periodically call the `get_charges` tool. You can then stream the results directly into a chart or graph component in your UI, giving users a live view of their Civo spending without needing to refresh the page.

It does. When you call an action like `reboot_instance`, you can design your app to poll for status updates. The Vercel AI SDK makes it easy to stream these updates so your UI can show the instance transitioning from 'running' to 'rebooting' and back again.

This server only handles your Civo API key to authenticate requests. The key is encrypted at rest and only used for calls your agent makes. Data like instance IPs or cluster details passes through our ephemeral V8 isolates but is never logged or stored by Vinkius.

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