How to Use the Image-Charts MCP in Vercel AI SDK

Q: Can Image-Charts and Vercel AI SDK handle large datasets?

Yes. Use the renderchartpost tool to send data as a POST request, which avoids the URL length limits that plague standard GET-based images.

Stream Image-Charts visuals directly into your Vercel AI SDK frontends for instant, real-time data rendering.

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Connect Image-Charts MCP to Vercel AI SDK

Create your Vinkius account to connect Image-Charts 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-Charts with Vercel AI SDK

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Live chart generation in the Vercel AI SDK

Pipe raw data straight into your UI using `generate_chart_url`. It builds a lightweight GET request that fits perfectly into your standard rendering flow. Your users won't stare at loading spinners. The image renders as soon as the agent finishes its response, keeping the interface snappy and responsive.

Handle massive datasets via POST

When your data exceeds the 2KB limit, switch to `render_chart_post`. It handles larger payloads by returning a Base64 Data URI that you can inject directly into your image tags. This bypasses URL length restrictions entirely. It ensures your charts display correctly even when you are pushing complex, multi-point datasets to the client.

Native MCP Server integration

Connect this MCP Server to your project using the standard transport configuration. The SDK manages the handshake so you can focus on building the view layer. It works seamlessly with edge functions, keeping your latency low. You gain instant access to charting tools without bloating your bundle with third-party visualization libraries.

Setup guide

Set up Image-Charts 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-Charts 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-Charts 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 Image-Charts. 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-Charts MCP in Vercel AI SDK

Install the MCP client and pass the tools to your generateText or streamText function. It wires up the server to your agents in just a few lines of code.

Yes. Use the `render_chart_post` tool to send data as a POST request, which avoids the URL length limits that plague standard GET-based images.

It does. Because the server uses standard HTTP transport, it fits right into your edge infrastructure without blocking your request execution.

Your data is processed only to generate the requested visualization. No records are kept, and the images are returned as ephemeral Base64 strings.

You just need your endpoint token. Once that is set in the Vinkius dashboard, your agent gains secure access to the tools.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.