Can I check the status of a specific invoice?

Yes! Use the `get_invoice_details` tool with the unique invoice ID. The agent will return the full record, including the current balance and payment status.

How do I see all active subscriptions?

Use the `list_billing_subscriptions` tool. Your agent will fetch all customer packages, allowing you to filter for those that are currently in an active state.

Where do I find my API Public and Private keys?

Log in to your ChargeOver account and navigate to **Settings > Developer > REST API**. You can generate and copy your keys from that section.

ChargeOver MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: ChargeOver
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect ChargeOver 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 ChargeOver "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in ChargeOver?"
    )
    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 ChargeOver MCP Server

Connect your ChargeOver account to any AI agent and take full control of your recurring billing and invoicing operations through natural conversation. Streamline how you manage subscriptions and customer payments.

Pydantic AI validates every ChargeOver tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

Customer Oversight — List and retrieve details for all customer profiles and their contact information natively
Invoice Management — Monitor generated invoices and their current payment status flawlessly
Subscription Tracking — List and retrieve details for active and inactive customer packages securely
Transaction Auditing — Access and monitor all billing transactions and payment history flawlessly
Quote Control — List and review sales quotes to manage your revenue pipeline securely
Account Visibility — Retrieve core account and user information directly within your workspace

The ChargeOver MCP Server exposes 8 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 ChargeOver to Pydantic AI via MCP

Follow these steps to integrate the ChargeOver 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 8 tools from ChargeOver with type-safe schemas

Why Use Pydantic AI with the ChargeOver MCP Server

Pydantic AI provides unique advantages when paired with ChargeOver 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 ChargeOver integration code

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

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

ChargeOver + Pydantic AI Use Cases

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

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

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

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

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

ChargeOver MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect ChargeOver to Pydantic AI via MCP:

get_chargeover_account

Retrieve core account and user information

get_customer_details

Get detailed information for a specific customer

get_invoice_details

Get detailed information for a specific invoice

list_billing_quotes

List all sales quotes

list_billing_subscriptions

List all customer subscriptions (packages)

list_billing_transactions

List all billing transactions

list_chargeover_customers

List all customers

list_chargeover_invoices

List all invoices

Example Prompts for ChargeOver in Pydantic AI

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

"Show me the last 5 invoices in ChargeOver."

"List all customers with active subscriptions."

"What was my total transaction volume today?"

Troubleshooting ChargeOver MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

ChargeOver + Pydantic AI FAQ

Common questions about integrating ChargeOver 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 ChargeOver MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.