How to Use the Invoiced MCP in Pydantic AI

Q: How do I initialize the Invoiced MCP Server in Pydantic AI?

Install the package with pip install "pydantic-ai-slimmcp". Use the unified MCPToolset constructor pointing to your Vinkius HTTP endpoint, then pass it directly to your agent.

Build type-safe billing workflows with Pydantic AI that validate Invoiced schemas at runtime to prevent silent data corruption.

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Connect Invoiced MCP to Pydantic AI

Create your Vinkius account to connect Invoiced 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 Invoiced with Pydantic AI

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Strict invoice validation with Pydantic AI

`list_invoices` returns structured billing payloads that the framework validates against runtime schemas. If a field type changes or comes back empty, the agent fails immediately instead of processing bad data. You can safely query `get_invoice` to audit specific transactions. The framework guarantees that every field, from tax rates to line-item totals, strictly matches your Python models.

Type-safe customer record retrieval

`get_customer` fetches contact profiles, balances, and payment settings with strict type guarantees. This prevents your agent from hallucinating email addresses or account numbers during outreach. Starting your workflow with `list_customers` ensures you map every account ID to a valid model. Any schema drift on the API side triggers a loud validation error, protecting downstream systems.

Rigorous product catalog checks

This MCP Server uses `list_items` to retrieve your complete billing inventory with guaranteed type safety. The agent cross-references item codes and unit prices directly against your internal database models. It runs `list_plans` and `list_tax_rates` to verify subscription configurations. Because the validation is model-agnostic, you can use these tools safely with any supported LLM backend.

Setup guide

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

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

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

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Common questions about Invoiced MCP in Pydantic AI

Install the package with `pip install "pydantic-ai-slim[mcp]"`. Use the unified `MCPToolset` constructor pointing to your Vinkius HTTP endpoint, then pass it directly to your agent.

No, you should avoid the deprecated class. The unified toolset connects your agent to the MCP Server, letting you access tools like `list_subscriptions` and `list_payments`.

The framework will raise a validation error at runtime. This prevents your agent from making decisions based on malformed data when calling tools like `get_invoice`.

Yes, the framework is model-agnostic. You can run tools like `list_plans` using local models or commercial LLMs like Anthropic and OpenAI.

Your customer details, subscription plans, and tax rates are protected by Vinkius's zero-trust infrastructure. The server runs in an isolated V8 sandbox, and your API keys are managed securely without ever exposing them to the agent.

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