ChargeOver MCP Server for Pydantic AIGive Pydantic AI instant access to 7 tools to Create Billing Customer, Create Billing Invoice, Create Subscription, and more
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.
Ask AI about this App Connector for Pydantic AI
The ChargeOver app connector for Pydantic AI is a standout in the Finance Accounting category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 "
"(7 tools)."
),
)
result = await agent.run(
"What tools are available in ChargeOver?"
)
print(result.data)
asyncio.run(main())
* 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 revenue and subscription billing workflows through natural conversation.
Pydantic AI validates every ChargeOver tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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
- Billing Profile Orchestration — List and manage customer billing profiles programmatically, retrieving detailed high-fidelity account metadata and payment history
- Subscription Lifecycle Management — Create and update recurring billing packages programmatically to maintain perfectly coordinated subscriber journeys
- Invoice & Statement Architecture — Monitor real-time invoice history and programmatically generate new billing statements to streamline your accounts receivable
- Transaction Intelligence — Track payment transactions, refunds, and credits in real-time to maintain a high-fidelity overview of your financial health
- Operational Monitoring — Access high-level billing summaries and manage account-level metadata directly through your agent for instant financial reporting
The ChargeOver MCP Server exposes 7 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.
All 7 ChargeOver tools available for Pydantic AI
When Pydantic AI connects to ChargeOver through Vinkius, your AI agent gets direct access to every tool listed below — spanning recurring-invoicing, dunning-management, payment-collection, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new customer
Create a new invoice
Create a new subscription
List all customers
List all invoices
List all transactions
List all subscriptions (packages)
Connect ChargeOver to Pydantic AI via MCP
Follow these steps to wire ChargeOver into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
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
Example Prompts for ChargeOver in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with ChargeOver immediately.
"List all active billing customers in ChargeOver."
"Show the last 5 payment transactions and their status."
"Create a new subscription for 'Acme Corp' (ID: '1024') titled 'Pro Plan'."
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
pip install --upgrade pydantic-aiChargeOver + Pydantic AI FAQ
Common questions about integrating ChargeOver MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.