How to Use the iLovePDF MCP in OpenAI Agents SDK

Get your OpenAI Agents SDK pipelines compressing and merging documents directly through the iLovePDF API with zero manual steps.

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Connect iLovePDF MCP to OpenAI Agents SDK

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

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Automate document pipelines with OpenAI Agents SDK

This MCP Server lets your OpenAI agent initialize processing workflows using `start_pdf_task` and feed files straight into the pipeline via `upload_pdf_by_url`. The agent tracks the execution state using `get_task_status` and triggers the actual operation with `process_pdf_task`. You get a clean, hands-off pipeline that handles high-volume document runs without human intervention.

Secure agent handoffs for complex document runs

You can set up a routing agent that handles file ingestion and then hands off to a compression specialist using `upload_pdf_by_url` and `process_pdf_task`. Built-in OpenAI tracing monitors these handoffs in real-time on your dashboard. You can watch the entire flow from initial task creation to the moment the agent calls `get_pdf_download_link` to retrieve the final file.

Guardrails prevent unauthorized iLovePDF operations

The `process_pdf_task` tool requires strict boundaries when running agents in production to avoid runaway API costs. If an agent attempts to call `list_pdf_tasks` without proper authorization, the SDK block mechanism intercepts the call. This keeps your document workflows safe while still giving the agent access to `get_pdf_download_link` when tasks complete.

Setup guide

Set up iLovePDF 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 iLovePDF tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate iLovePDF 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="iLovePDF Agent",
            instructions="You have access to iLovePDF tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 iLovePDF. 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 iLovePDF MCP in OpenAI Agents SDK

Install the package using pip, then configure the streamable HTTP server parameters with your Vinkius endpoint. Pass this server instance inside the agent constructor list to let your agent auto-discover the document tools.

Yes, you can design one agent to start the process and another to monitor it. The first agent calls `start_pdf_task` and passes the task ID to a monitoring agent, which polls `get_task_status` until completion.

You configure native guardrails within the SDK to intercept MCP Server tool calls before execution. This lets you inspect parameters for `process_pdf_task` and block any requests that exceed your defined budget.

Once the task status returns a successful state, have your agent call `get_pdf_download_link`. This returns a direct URL to retrieve your processed document without hosting files locally.

No, the Vinkius sandbox operates with zero-trust ephemeral storage. Your PDF documents and file URLs are processed directly by the API and are purged from the sandbox environment once the execution ends.

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