How to Use the Gelato MCP in Pydantic AI

Q: Can my Pydantic AI agent handle Gelato order tracking safely?

Yes, your agent can call getorderstatus or getordershipments to check delivery progress. The returned tracking strings are validated against strict string patterns to ensure data integrity.

Q: Does this setup support checking the connection before running print jobs?

You can run verifyapiconnection at startup to confirm your credentials are valid. Pydantic AI validates the boolean response to ensure the server is fully operational.

Stop silent print errors by validating your Gelato MCP Server payloads with Pydantic AI.

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Connect Gelato MCP to Pydantic AI

Create your Vinkius account to connect Gelato to Pydantic AI 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 Gelato with Pydantic AI

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Validate Gelato MCP Server payloads before printing

Running order tools like `create_print_order` through your Pydantic AI agent guarantees structured data validation. A single malformed shipping address can ruin a print-on-demand order, but this framework guarantees that every parameter conforms strictly to your defined Python schemas before the API call is made. If your Pydantic AI agent generates an invalid zip code, the framework rejects the execution immediately. Preventing bad data from ever reaching the Gelato fulfillment network saves you from failed delivery charges.

Parse product catalogs into strict Python models

Parsing catalog tools like `list_catalog_products` through your Pydantic AI validation engine keeps your data clean. When your agent calls `list_catalog_products` or `get_product_details`, Pydantic AI parses the raw JSON responses into typed Python models at runtime. Your print application will never deal with silent changes in product metadata or missing fields. If the Gelato catalog structure changes, your Pydantic AI app raises a validation error immediately so you can fix it.

Ensure shipping quotes match strict business schemas

Sourcing pricing tools like `get_shipping_quote` directly inside your Pydantic AI agent keeps your margins secure. Your agent can pull real-time rates, which Pydantic AI validates against your internal margin models. The Pydantic AI framework ensures that the response contains all required price fields before passing it to your pricing engine. This protects your print margins from corrupted API responses or unexpected null values.

Setup guide

Set up Gelato MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "gelato-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Gelato tools.",
)

result = await agent.run("List recent Gelato transactions")
print(result.output)

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Common questions about Gelato MCP in Pydantic AI

Initialize an MCPToolset with your Vinkius MCP Server endpoint URL. Pass this toolset instance inside the toolsets list when constructing your Pydantic AI agent.

The framework will immediately raise a validation error instead of passing dirty data to your model. This prevents your agent from hallucinating properties when reading catalogs with `list_catalog_products`.

Yes, your agent can call `get_order_status` or `get_order_shipments` to check delivery progress. The returned tracking strings are validated against strict string patterns to ensure data integrity.

You can run `verify_api_connection` at startup to confirm your credentials are valid. Pydantic AI validates the boolean response to ensure the server is fully operational.

All recipient addresses and order payloads are processed within memory inside Vinkius's isolated sandbox. We do not store any of your customer's personal data on persistent disks.

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