Gelato MCP Server for AutoGen 12 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Gelato as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="gelato_agent",
tools=tools,
system_message=(
"You help users with Gelato. "
"12 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
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.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Gelato tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
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 AutoGen 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 AutoGen via MCP
Follow these steps to integrate the Gelato MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 12 tools from Gelato automatically
Why Use AutoGen with the Gelato MCP Server
AutoGen provides unique advantages when paired with Gelato through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Gelato tools to solve complex tasks
Role-based architecture lets you assign Gelato tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Gelato tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Gelato tool responses in an isolated environment
Gelato + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Gelato MCP Server delivers measurable value.
Collaborative analysis: one agent queries Gelato while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Gelato, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Gelato data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Gelato responses in a sandboxed execution environment
Gelato MCP Tools for AutoGen (12)
These 12 tools become available when you connect Gelato to AutoGen 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 AutoGen
Ready-to-use prompts you can give your AutoGen 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 AutoGen
Common issues when connecting Gelato to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Gelato + AutoGen FAQ
Common questions about integrating Gelato MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Gelato to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.