How to Use the Leonardo.ai (Generative AI & Models) MCP in Vercel AI SDK

Stream high-fidelity images directly into your Vercel AI SDK interface using the Leonardo.ai (Generative AI & Models) MCP Server.

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Connect Leonardo.ai (Generative AI & Models) MCP to Vercel AI SDK

Create your Vinkius account to connect Leonardo.ai (Generative AI & Models) 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 Leonardo.ai (Generative AI & Models) with Vercel AI SDK

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Claude

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Real-time image generation in Vercel AI SDK

Trigger `generate_image` from your edge functions to pipe visual output straight to your React or Svelte components. You get the generation ID immediately, letting you update your UI state while the image renders. Use `get_generation` to poll for completion and display the final asset without blocking your main thread. It is built for developers who need live visual feedback for their users.

Visual asset auditing with Vercel AI SDK

Query `list_user_generations` to pull your recent image history directly into your dashboard. You can quickly filter and display past work without manual database lookups. Execute `delete_generation` to clean up your workspace directly from the frontend. This keeps your storage usage predictable and your UI uncluttered.

Model discovery within Vercel AI SDK

Call `list_platform_models` to populate dropdowns or selectors in your application. This gives your users instant access to the latest global models available on the platform. Retrieve technical specs via `get_model` to adjust your prompting strategy dynamically. Your application logic stays synced with the latest available model parameters.

Setup guide

Set up Leonardo.ai (Generative AI & Models) 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 Leonardo.ai (Generative AI & Models) 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 Leonardo.ai (Generative AI & Models) transactions",
});

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Leonardo.ai. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Leonardo.ai (Generative AI & Models) MCP in Vercel AI SDK

Install the required packages and initialize the client using your endpoint. Pass the tools retrieved from the server into your `generateText` or `streamText` functions to allow your AI client to execute them.

Yes. Use the list tools to fetch your generation history and map the image URLs to your frontend components. You can manage the entire display lifecycle programmatically.

The server provides the necessary ID and status data that your streaming functions need. You can handle the asynchronous nature of image generation by updating your UI as the status changes.

The Vercel AI SDK supports standard auth providers. You pass your endpoint token via the configuration to ensure secure communication between your application and the server.

Your images and generation history are stored securely on the platform. The server only transmits the metadata and URLs required to render your content in the browser.

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