Gelato MCP Server for OpenAI Agents SDK 12 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Gelato through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Gelato Assistant",
instructions=(
"You help users interact with Gelato. "
"You have access to 12 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Gelato"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Gelato MCP Server
Connect your Gelato account to any AI agent to automate your print-on-demand (POD) lifecycle through the Model Context Protocol (MCP). Gelato enables creators and businesses to produce and ship custom products globally without inventory. This MCP server allows you to manage orders, retrieve product catalogs, and track real-time shipping statuses directly through natural conversation.
The OpenAI Agents SDK auto-discovers all 12 tools from Gelato through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Gelato, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
Key Features
- Order Management — List all print orders, fetch detailed status metadata, and create new global orders programmatically.
- Product Discovery — Access available product catalogs and retrieve detailed specifications for individual items (product UIDs).
- Fulfillment Tracking — Retrieve tracking numbers and real-time shipment details for every order in your account.
- Pricing & Quoting — Request real-time shipping and production quotes for potential orders across different regions.
- Webhook Visibility — List configured webhooks to ensure your internal systems are receiving real-time production updates.
- Account Oversight — Verify your account metadata and API connectivity to maintain a seamless production workflow.
- Global Fulfillment — Leverage Gelato's massive network of local production partners directly from your chat interface.
The Gelato MCP Server exposes 12 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Gelato to OpenAI Agents SDK via MCP
Follow these steps to integrate the Gelato MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 12 tools from Gelato
Why Use OpenAI Agents SDK with the Gelato MCP Server
OpenAI Agents SDK provides unique advantages when paired with Gelato through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Gelato + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Gelato MCP Server delivers measurable value.
Automated workflows: build agents that query Gelato, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Gelato, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Gelato tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Gelato to resolve tickets, look up records, and update statuses without human intervention
Gelato MCP Tools for OpenAI Agents SDK (12)
These 12 tools become available when you connect Gelato to OpenAI Agents SDK via MCP:
cancel_print_order
Cancel an order
create_print_order
Place new order
get_account_info
Get account identity
get_order_shipments
Track shipments
get_order_status
Get order details
get_product_details
Get product metadata
get_shipping_quote
Request a quote
list_catalog_products
List products in catalog
list_print_orders
List all orders
list_print_webhooks
List webhook configs
list_product_catalogs
List product catalogs
verify_api_connection
Check connection
Example Prompts for Gelato in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Gelato immediately.
"List all my active print orders and their current status."
"Get the shipping details for order 'gelato_12345'."
"List all products in the 'Apparel' catalog (ID: cat_987)."
Troubleshooting Gelato MCP Server with OpenAI Agents SDK
Common issues when connecting Gelato to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Gelato + OpenAI Agents SDK FAQ
Common questions about integrating Gelato MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Gelato with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Gelato to OpenAI Agents SDK
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.