How to Use the Billit MCP in Pydantic AI

Ensure type-safe accounting with Pydantic AI and Billit by validating every invoice and party response at runtime.

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Connect Billit MCP to Pydantic AI

Create your Vinkius account to connect Billit 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 Billit with Pydantic AI

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Validate Billit data with Pydantic AI

Every response from `get_invoice` is checked against your models. If the API structure shifts, your agent throws an error instead of continuing with bad data. You gain total confidence in the integrity of your accounting records. It stops silent errors before they reach your database.

Automate Billit workflows using Pydantic AI

Your agent sequences `list_parties` and `create_invoice` calls to handle customer billing cycles. The type-safe responses make chaining these calls trivial. You'll define the expected schema for your invoice objects. The MCP Server ensures the data coming back matches your requirements exactly.

Use Pydantic AI to query Billit

Call `list_expenses` to get a structured list of your spend. Your agent parses these into Python objects for immediate analysis. This approach eliminates the need for manual parsing logic. You simply declare the type and let the agent handle the rest.

Setup guide

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

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

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

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Common questions about Billit MCP in Pydantic AI

It matches the JSON output against your defined Pydantic models. If the fields don't align, the agent fails immediately.

Yes, the toolset is model-agnostic. It works perfectly with local models so long as they support tool calling.

It supports both SSE and Streamable HTTP. You just point the toolset at your live server URL.

Pydantic AI catches the validation error. Your agent won't hallucinate fields that aren't there.

Your financial figures are validated and processed in-memory. We never log your invoice values or private tax info in the MCP transport layer.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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