How to Use the Transloadit MCP in OpenAI Agents SDK

Q: What is the best way to manage files using Transloadit and the OpenAI Agents SDK?

Start by defining a reusable workflow blueprint with createprocessingtemplate. Then, when you need it executed, your agent calls createassembly referencing that template. It keeps your code clean and focused on logic.

Q: Can the OpenAI Agents SDK help me audit past job performance using Transloadit?

Absolutely. After a job runs, you can use getassemblydetails to check its status and results. You can also run listassemblies to see a history of every assembly your agent has triggered.

Q: If I need usage reports for Transloadit with the OpenAI Agents SDK, which tool do I use?

You call getbillingusage, passing the month in YYYY-MM format. This tells you exactly what file processing usage and costs were generated during that billing cycle.

Manage media pipelines easily with the OpenAI Agents SDK. Automate video encoding and file processing for your agent.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

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.

GDPR Free for Subscribers

Setup Transloadit with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automated Media Processing Pipelines

Need to encode a batch of videos or resize images? You build this workflow by calling `create_assembly`, feeding it a JSON steps definition. The system handles the whole pipeline, letting your agent manage complex media tasks without writing boilerplate code. You can also check what's running and see results using `list_assemblies` or get status updates on specific jobs via `get_assembly_details`. It’s a full lifecycle view for any file processing job.

Template Management

Don't rebuild the same process over and over. Use `create_processing_template` to build reusable JSON blueprints for your media tasks—say, 'resize-profile-pic'. This template can then be referenced when you call `create_assembly`. It’s smart; it keeps complex logic separated from execution. The system also lets you audit what templates exist with `list_templates`, or if you messed up and need to wipe one out completely using `delete_template`.

Usage and Cost Tracking

When your agent is running production workloads, you gotta track the bill. The tool `get_billing_usage` takes a YYYY-MM month and spits out exactly how much file processing usage and costs you incurred. This helps keep things accountable. For deeper debugging or auditing purposes, `list_assemblies` shows all recent job runs in your account. If you need to re-run an old successful job, just use `replay_assembly`.

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())

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 Transloadit. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Transloadit now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Transloadit MCP in OpenAI Agents SDK

You pass the MCP Server object directly into your Agent constructor. This makes all of Transloadit's tools—like `create_assembly`—auto-discoverable by your agent without any custom coding required.

Start by defining a reusable workflow blueprint with `create_processing_template`. Then, when you need it executed, your agent calls `create_assembly` referencing that template. It keeps your code clean and focused on logic.

Absolutely. After a job runs, you can use `get_assembly_details` to check its status and results. You can also run `list_assemblies` to see a history of every assembly your agent has triggered.

You call `get_billing_usage`, passing the month in YYYY-MM format. This tells you exactly what file processing usage and costs were generated during that billing cycle.

This server handles billing data, specifically reporting on file processing usage and costs. The `get_billing_usage` tool provides this monthly financial breakdown for your account.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript