How to Use the Simple Fatoora MCP in Pydantic AI

Q: Can I use Simple Fatoora to create VAT invoices with Pydantic AI?

You call createvatinvoice using the toolset. The output is strongly typed, meaning you can trust that the tax rates and fields are exactly what your model expects.

Q: What if I use Simple Fatoora to list items with Pydantic AI?

You'll get a predictable JSON structure from listitems. The data type for the item name, ID, and price will always match your defined Pydantic fields.

Q: Can I retrieve historical invoices using Simple Fatoora with Pydantic AI?

Sure thing. You run listinvoices to get IDs, then pass those to getinvoice. The resulting data will be validated against your defined schema.

Simple Fatoora for Pydantic AI: Type-safe invoicing with guaranteed data validation.

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Create your Vinkius account to connect Simple Fatoora to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Simple Fatoora with Pydantic AI

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Manage Client Records

The `list_clients` tool pulls a structured list of all active clients. You can then use `get_client` to pull specific details, knowing the response will match your expected Pydantic model. If you need a new client entry, call `create_client`. The system validates the incoming data against predefined schemas before saving it.

Generate B2B VAT Invoices

To handle corporate sales, your agent calls `create_vat_invoice`. This guarantees ZATCA-compliant output, including automated tax calculations and the necessary QR code data. For less formal transactions, use `create_simplified_invoice` to generate B2C receipts. The structure is always validated.

Maintain Product Catalog

The `list_items` tool gives you a defined list of all products and services. Every item record is typed, so there's no guesswork. When adding new goods or services, use `create_item`. The Pydantic validation ensures that every field (like price or unit) has the correct data type.

Setup guide

Set up Simple Fatoora 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": {
        "simple-fatoora-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Simple Fatoora MCP in Pydantic AI

Every MCP response is validated against your Python models at runtime. If Simple Fatoora sends back unexpected data, your agent fails loud and clear—no silent corruption.

You call `create_vat_invoice` using the toolset. The output is strongly typed, meaning you can trust that the tax rates and fields are exactly what your model expects.

You'll get a predictable JSON structure from `list_items`. The data type for the item name, ID, and price will always match your defined Pydantic fields.

Sure thing. You run `list_invoices` to get IDs, then pass those to `get_invoice`. The resulting data will be validated against your defined schema.

The server handles core identity fields: names, addresses, Tax IDs, and contact information. It keeps billing details separate from actual payment credentials.

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