How to Use the Image Router MCP in Vercel AI SDK

Q: How does Image Router select the best model for a Vercel AI SDK prompt?

The server uses generateimage to parse your prompt's style and quality requirements against live model metadata. It matches the text to the most cost-effective engine without manual routing code in your Next.js API route.

Q: Can I use Image Router to handle variations in Vercel AI SDK?

Yes, you call generatevariation through the SDK to spin up alternative versions of an image. The MCP Server determines which model is best equipped to handle the variation based on the original image's style parameters.

Q: How do I list available models in my frontend?

You use listmodelsbycategory to get a structured list of active models. The Vercel AI SDK maps these models directly to your UI components so users can filter by category.

Let your Vercel AI SDK app automatically route image generation to the best model with this fast MCP Server.

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Connect Image Router MCP to Vercel AI SDK

Create your Vinkius account to connect Image Router 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 Image Router with Vercel AI SDK

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Automated image routing for Vercel AI SDK apps

The `generate_image` tool analyzes user prompts right inside your Next.js edge functions to pick the best model before the API call even fires. Forget about hardcoding model selection or writing complex fallback logic in your Vercel AI SDK codebase with this MCP Server. When users request adjustments, the `edit_image` tool modifies existing assets without losing the original context. This keeps your React UI fast by bypassing heavy model-selection overhead directly at the edge.

Dynamic style discovery and scaling

The `list_styles` tool fetches active art styles so your UI dropdowns update instantly without hardcoding static arrays. Your Vercel AI SDK client can query these styles on the fly to present valid options to the user. Once the user selects a style, `upscale_image` takes the low-res preview and blows it up to production size. This two-step process saves bandwidth and keeps your edge functions from timing out.

Real-time generation status tracking

The `get_generation_status` tool tracks ongoing image rendering tasks and streams the progress directly to your UI. This prevents empty loading spinners in your React components by feeding live status updates to the client. If a specific model times out, the `check_imagerouter_status` tool verifies endpoint health to let your application failover instantly. Your Vercel AI SDK app stays responsive even when third-party APIs go down.

Setup guide

Set up Image Router 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 Image Router 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 Image Router transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Image Router. 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 Image Router MCP in Vercel AI SDK

The server uses `generate_image` to parse your prompt's style and quality requirements against live model metadata. It matches the text to the most cost-effective engine without manual routing code in your Next.js API route.

Yes, you call `generate_variation` through the SDK to spin up alternative versions of an image. The MCP Server determines which model is best equipped to handle the variation based on the original image's style parameters.

No, the MCP Server runs its routing logic under 100ms to keep edge execution times low. It resolves the model target before the main generation API call starts.

You use `list_models_by_category` to get a structured list of active models. The Vercel AI SDK maps these models directly to your UI components so users can filter by category.

The server processes your image URLs and prompt strings within an ephemeral V8 sandbox. Your raw image files and text inputs are never stored on Vinkius servers, keeping your creative assets secure.

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