Can the AI automatically process a refund for a specific transaction ID?

Yes! Use the `create_transaction` tool with the 'refundTransaction' type. You'll need to provide the original transaction ID and the amount to be credited back to the customer.

How do I check for transactions that have not yet been settled?

Simply ask the agent to run the `get_unsettled_transaction_list` tool. It will return all transactions currently sitting in your unsettled queue for review.

Is it possible to manage customer payment profiles securely through the AI?

Yes. The `get_customer_profile` tool allows the agent to retrieve stored profiles (without exposing full sensitive card data), enabling you to manage recurring billing and saved information securely.

Authorize.net MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Authorize.net
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 Authorize.net 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 Authorize.net "
            "(10 tools)."
        ),
    )

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

Connect your Authorize.net merchant account to any AI agent and manage your entire payment lifecycle through natural conversation.

Pydantic AI validates every Authorize.net 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

Transaction Management — Authorize, capture, refund, and void transactions with full audit trails and security
Financial Reporting — List transactions from settled batches, unsettled queues, and analyze processing performance
Customer Profiles — Retrieve and manage secure customer payment information and subscription profiles
Batch Insights — Monitor daily settlement statistics and high-level performance metrics for your merchant account

The Authorize.net 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 Authorize.net to Pydantic AI via MCP

Follow these steps to integrate the Authorize.net 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 Authorize.net with type-safe schemas

Why Use Pydantic AI with the Authorize.net MCP Server

Pydantic AI provides unique advantages when paired with Authorize.net 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 Authorize.net integration code

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

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

Authorize.net + Pydantic AI Use Cases

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

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

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

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

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

Authorize.net MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Authorize.net to Pydantic AI via MCP:

create_transaction

You must provide the transaction type (e.g., authCaptureTransaction) and the request body. Create a new payment transaction

get_batch_statistics

Get statistics for a specific batch

get_customer_profile

Retrieve a customer profile by ID

get_settled_batch_list

Retrieve a list of settled batches for a date range

get_transaction_details

Get complete information for a specific transaction

get_transaction_list

List transactions for a specific settled batch

get_unsettled_transaction_list

List the most recent unsettled transactions

list_customer_profiles

Retrieve a list of all customer profile IDs

refund_transaction

Refund a settled transaction

void_transaction

Void an unsettled transaction

Example Prompts for Authorize.net in Pydantic AI

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

"List the most recent unsettled transactions."

"Refund $50.00 for transaction ID '123456789'."

"Show the settlement statistics for the last closed batch."

Troubleshooting Authorize.net MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Authorize.net + Pydantic AI FAQ

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