How to Use the Flystack MCP in Vercel AI SDK

Q: Can I use Flystack tools to debug Vercel AI SDK app issues?

You can use listflystackclusters to see where your services are running. It lets you correlate app behavior with cluster health.

Stream real-time infrastructure telemetry into your Vercel AI SDK interface without waiting for background processes.

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…and any MCP-compatible client

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Connect Flystack MCP to Vercel AI SDK

Create your Vinkius account to connect Flystack 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 Flystack with Vercel AI SDK

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Live infrastructure status in Vercel AI SDK

Feed your UI live diagnostics by piping `check_api_status` directly into your stream. Your frontend reacts to the infrastructure state as it happens instead of waiting for a slow backend response. This keeps your users informed while the agent handles the heavy lifting. The data flows over the wire and hits the DOM instantly.

Fetch metrics without blocking

Use `get_cluster_metrics` to pull performance data into your dashboard components. Since the output streams, your charts update while the agent is still gathering the rest of the payload. Your users watch the numbers tick up. It removes the friction of loading screens in your Vercel AI SDK applications.

Audit deployments on the fly

Call `get_deployment_details` to verify environment configurations before your agent makes a move. You get the full object back as a string, ready for your components to parse. This makes your AI smarter about what's actually running. It turns raw deployment data into actionable UI elements.

Setup guide

Set up Flystack 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 Flystack 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 Flystack transactions",
});

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

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Common questions about Flystack MCP in Vercel AI SDK

Install the MCP packages and point the client to your server URL. You then inject the tools into your stream handler to start pulling data.

Yes. The tools output standard text results that integrate with the SDK's streaming pipeline. You get the raw data as it arrives.

You can use `list_flystack_clusters` to see where your services are running. It lets you correlate app behavior with cluster health.

The server returns an error code that your client handles as a standard rejection. You should wrap your calls in a try-catch block.

We only touch your deployment IDs and cluster telemetry metrics. Your traffic is encrypted, and no sensitive source code ever leaves your environment.

Use it with your favorite AI tools

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