Can I preview how much a customer will be charged before updating their subscription?

Yes. The `preview_subscription` tool simulates a run of the billing engine for a specific subscription ID. Your AI agent will return the projected charges and billing dates without committing any actual changes to the account.

How do I see the invoice history for a specific billing account?

You can use the `get_invoices` tool. Provide the unique Zuora account ID or number, and your agent will retrieve a list of all invoices generated for that customer, helping you audit their billing history.

Is it possible to update a customer's billing contact info via chat?

Absolutely. Using the `update_account` tool, you can provide a JSON payload with updated fields (e.g., billing email or address) for a specific account ID, and your agent will apply the changes in Zuora instantly.

Zuora MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Zuora
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Zuora through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Zuora "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Zuora?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Zuora MCP Server

Connect your Zuora account to any AI agent and manage your enterprise monetization infrastructure through natural conversation.

Pydantic AI validates every Zuora tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Subscription Lifecycle — List all active and historical subscriptions for any account and retrieve deep details including rate plan charges
Billing Account Management — Create new billing accounts, retrieve full account metadata, and update customer profiles directly from your agent
Unified Orders — Create and manage complex Zuora Orders for subscriptions, renewals, or amendments using structured JSON payloads
Product Catalog Discovery — Browse your entire billable product catalog and available rate plans to understand your monetization inventory
Invoice Auditing — List and monitor all generated invoices for a specific account to track billing history and payment requirements
Billing Engine Simulation — Preview subscription charges and generate quotes to verify billing logic before committing any changes
Deep Discovery — Quickly find unique account, subscription, and order IDs required for automated revenue operations workflows

The Zuora MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Zuora to Pydantic AI via MCP

Follow these steps to integrate the Zuora MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Zuora with type-safe schemas

Why Use Pydantic AI with the Zuora MCP Server

Pydantic AI provides unique advantages when paired with Zuora through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Zuora integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Zuora connection logic from agent behavior for testable, maintainable code

Zuora + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Zuora MCP Server delivers measurable value.

Type-safe data pipelines: query Zuora with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Zuora tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Zuora and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Zuora responses and write comprehensive agent tests

Zuora MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Zuora to Pydantic AI via MCP:

create_account

Create a new billing account

create_order

Create a Zuora unified Order

get_account

Get account details

get_invoices

Get invoices for an account

get_order

Get order details

get_subscription

Get subscription details

list_products

List product catalog

list_subscriptions

List account subscriptions

preview_subscription

Preview subscription charges

update_account

Update account details

Example Prompts for Zuora in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Zuora immediately.

"List all active subscriptions for account ID 'acc-123'."

"Show me the last 3 invoices for 'Acme Corp'."

"Preview the charges for subscription 'S-00001'."

Troubleshooting Zuora MCP Server with Pydantic AI

Common issues when connecting Zuora to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Zuora + Pydantic AI FAQ

Common questions about integrating Zuora MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Zuora MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.