How to Use the Zid MCP in Pydantic AI

Q: How do I list all orders using Zid with Pydantic AI?

Call listzidorders within the toolset. The resulting list is immediately validated against your schema, so you know exactly what fields to expect for every order record.

Ensure perfect data integrity for Zid e-commerce. Type-safe agents using Pydantic AI guarantees correct results every time.

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Connect Zid MCP to Pydantic AI

Create your Vinkius account to connect Zid 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 Zid with Pydantic AI

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Validate Customer Records

If you call `get_zid_customer`, Pydantic ensures the response fields match exactly what your model expects. There's no guessing game here. The agent can list all shop clients via `list_zid_customers` and validate that every returned record fits your defined data schema.

Check Product Details Safely

When fetching product info with `get_zid_product`, the response is validated at runtime. If Zid sends unexpected JSON, the agent fails loudly—you know immediately something's wrong. Use `list_zid_products` to get a type-safe list of all available items for your application.

Process Order Data with Reliability

The Pydantic AI framework makes dealing with orders rock solid. Calling `get_zid_order` returns data that adheres strictly to your Python models, preventing silent corruption. You can also use `list_zid_orders` and `get_zid_shop_profile`, knowing the structure of the returned object is guaranteed.

Setup guide

Set up Zid 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": {
        "zid-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Zid MCP in Pydantic AI

Pydantic validates every single response from the MCP Server. This means when your agent calls `list_zid_products` or any other tool, you're guaranteed to get data that matches your Python type definitions.

You can securely handle customer lists, product inventories (`list_zid_inventories`), and transaction records. The benefit is knowing the exact structure of every piece of e-commerce data.

Yes, massively. It eliminates silent failures. If the underlying API changes or returns bad data, your agent doesn't break mysteriously; it throws a clear validation error you can fix.

Call `list_zid_orders` within the toolset. The resulting list is immediately validated against your schema, so you know exactly what fields to expect for every order record.

This MCP Server touches customer and transaction data. Because the data is strictly typed, it helps ensure that sensitive identifiers are processed and logged correctly within your application's defined model.

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