How to Use the Urlbox MCP in OpenAI Agents SDK

Q: Does Urlbox integrate well with structured data processing in the OpenAI Agents SDK?

Yes. You can use getmetadata first to pull structured source data, and then pass that context along with a visual asset generated by the MCP Server for your agents to analyze together.

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Connect Urlbox MCP to OpenAI Agents SDK

Create your Vinkius account to connect Urlbox to OpenAI Agents 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 Urlbox with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Capture Web Screenshots

You need multiple views of a single URL. Your agents can take standard images with `take_screenshot` or grab mobile-specific versions using `take_mobile_screenshot`. For maximum fidelity, the tool offers `take_retina_screenshot`, giving you high-resolution assets for detailed visual review.

Convert URLs to PDFs

Instead of managing dozens of image files, just send a URL and get a fully rendered document. The `generate_pdf` tool handles this conversion, turning live web content into a single, printable PDF file that your agents can immediately process for reporting.

Extract Web Metadata

Before taking pictures, you might need context. Use the `get_metadata` tool to pull structured data about a URL itself (like title or description). This allows your agent system to validate source information against visual evidence captured by the MCP Server.

Setup guide

Set up Urlbox MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Urlbox tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Urlbox tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Urlbox tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Urlbox Agent",
            instructions="You have access to Urlbox tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Urlbox MCP in OpenAI Agents SDK

You pass the MCP Server definition directly into your Agent constructor. Your agents automatically discover the available tools like `generate_pdf` and know exactly when to call them during a workflow.

Absolutely. The MCP Server offers three distinct screenshot methods: standard PNG capture (`take_screenshot`), mobile view emulation (`take_mobile_screenshot`), and high-DPI retina resolution capture (`take_retina_screenshot`).

This MCP Server primarily touches visual content (PNG/PDF files) and source text metadata. Your agents process these outputs, keeping the raw asset handling contained to the secure Vinkius environment.

Yes. You can use `get_metadata` first to pull structured source data, and then pass that context along with a visual asset generated by the MCP Server for your agents to analyze together.

The built-in guardrails validate every action. If an expected output type from `generate_pdf` is wrong, the system fails loudly and provides clear tracing via the OpenAI dashboard, making debugging simple.

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