How to Use the Urlbox MCP in Cursor

Q: How do I integrate Urlbox with Cursor?

You add the server configuration to your project's .cursor/mcp.json file. Once set up, the AI agent can call tools like renderselector directly while you write code in the same editor window.

Q: Does Urlbox support asynchronous rendering with Cursor?

Yes. The renderasync tool is available for background jobs, and its results are delivered via a webhook. This means your agent can kick off a long job and then continue coding while it waits.

Q: Can I list storage buckets with Urlbox and Cursor?

You can use liststoragebuckets to see what cloud storage containers are available. This helps the AI generate code that correctly targets where rendered assets should be saved.

Q: Is there a way to check usage with Urlbox and Cursor?

You can use getcreditusage to model costs directly into your application. The agent gets real-time stats, so you don't have to guess the pricing structure.

Inject live rendering context into your code using Cursor's MCP Server integration.

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Connect Urlbox MCP to Cursor

Create your Vinkius account to connect Urlbox to Cursor 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 Urlbox with Cursor

Ask AI about this MCP

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Claude

Perplexity

Get specific elements for coding.

The `render_selector` tool lets the AI call out a single, precise element from a webpage. You can feed that raw text output directly into your function, so you're not working with whole screenshots. This level of precision is what separates writing code from just documenting it. Use this when you need to pull specific data points for a database schema.

Manage and list webhooks.

Need your code to react when something happens? You can use `list_webhooks` to check which endpoints are already active. Furthermore, the server allows you to manage these connections so your application knows where to send data. This capability lets the AI generate boilerplate for webhook handling in your preferred language.

Capture content reliably.

Want a quick PNG or PDF of a URL? `capture_png` and `capture_pdf` handle that. But remember, if you're coding against it, the better option is often to use `render_selector` for maximum data cleanliness. The MCP Server makes sure the AI agent receives live API responses—no mock stubs allowed.

Setup guide

Set up Urlbox MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Urlbox MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Urlbox transactions." If the MCP tools are loaded correctly, Cursor will call the Urlbox tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "urlbox-alternative-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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 Urlbox. 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.

Why Choose Vinkius

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Common questions about Urlbox MCP in Cursor

You add the server configuration to your project's `.cursor/mcp.json` file. Once set up, the AI agent can call tools like `render_selector` directly while you write code in the same editor window.

Yes. The `render_async` tool is available for background jobs, and its results are delivered via a webhook. This means your agent can kick off a long job and then continue coding while it waits.

You can use `list_storage_buckets` to see what cloud storage containers are available. This helps the AI generate code that correctly targets where rendered assets should be saved.

You can use `get_credit_usage` to model costs directly into your application. The agent gets real-time stats, so you don't have to guess the pricing structure.

This server handles web content URLs, cloud storage bucket listings (`list_storage_buckets`), and usage metrics for billing purposes (`get_credit_usage`).

Use it with your favorite AI tools

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

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