How to Use the Transloadit MCP in OpenAI Agents SDK

Q: How do I manage file assemblies with Transloadit using the OpenAI Agents SDK?

Your agent uses listassemblies to see all active jobs. Then, it calls getassembly on any specific ID to check its status and retrieve results once the processing is done.

Q: Can I update templates with Transloadit using the OpenAI Agents SDK?

Yep. Your agent uses updatetemplate(templateid, newdata) to modify an existing processing rule without having to delete and recreate it. It's a clean way to iterate on your logic.

Q: What information can Transloadit provide about billing records using the OpenAI Agents SDK?

You use getbill(month) to retrieve the full billing details for any given month. This is critical data that helps you track resource usage across your production agents.

Q: Does Transloadit's MCP Server support re-running failed jobs with the OpenAI Agents SDK?

Absolutely. The replayassembly tool lets your agent take a job ID and restart that assembly, even if it finished and you need to run it again for testing.

Manage file workflows and process data with your OpenAI Agents SDK.

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Connect Transloadit MCP to OpenAI Agents SDK

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

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Monitor File Processing Status via MCP Server

Need to know what's going on with a big file job? Use `list_assemblies` to see every running or completed task. You can then call `get_assembly` right away, which gives you the current status and final results for a specific run. If something went wrong, don't sweat it. If an assembly finished but needs another look, `replay_assembly` lets your agent re-run it without having to manually restart everything.

Control Processing Templates with OpenAI Agents SDK

Your agents need reusable rules for file processing. Use `create_template` to build a new processing workflow, or call `get_template` and `list_templates` just to review what exists. If the template needs tweaking, `update_template` lets your agent make those changes instantly. Don't lose work. You can always use `delete_template` when a rule is obsolete, keeping your system clean and focused.

Audit Account Context and Billing Records

Before launching any complex job, check the API connection status using `get_me`. This simple call lets your agent confirm it's talking to the right account. You can also manage operational costs by calling `get_bill` to retrieve billing info for a specific month. Keeping track of resources is key in production code. The MCP Server handles all this context retrieval so your agents don't get tripped up on setup.

Setup guide

Set up Transloadit 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 Transloadit tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Transloadit 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="Transloadit Agent",
            instructions="You have access to Transloadit 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 Transloadit MCP in OpenAI Agents SDK

Your agent uses `list_assemblies` to see all active jobs. Then, it calls `get_assembly` on any specific ID to check its status and retrieve results once the processing is done.

Yep. Your agent uses `update_template(template_id, new_data)` to modify an existing processing rule without having to delete and recreate it. It's a clean way to iterate on your logic.

You use `get_bill(month)` to retrieve the full billing details for any given month. This is critical data that helps you track resource usage across your production agents.

Absolutely. The `replay_assembly` tool lets your agent take a job ID and restart that assembly, even if it finished and you need to run it again for testing.

The server primarily touches file processing metadata and financial billing information. This includes assembly IDs, template definitions, and monthly usage records.

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