Can I process a refund for a transaction using the agent?

Yes! Use the `refund_transaction` tool with the Transaction Node ID. You can also specify a partial amount if you don't want to refund the full charge.

How do I capture a previously authorized transaction?

Simply ask the agent to `capture_transaction` and provide the Transaction Node ID. The funds will be captured and the status updated in your Braintree account.

Does the integration allow searching for a customer by email?

Yes. Use the `search_customers` tool and provide the exact email address. The agent will execute a GraphQL query to find the matching customer profile.

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

Name: Braintree
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 Braintree through the 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 Braintree "
            "(8 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Braintree MCP Server

Connect your Braintree gateway account to any AI agent and orchestrate your global payment and checkout workflows through natural conversation.

Pydantic AI validates every Braintree tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through the 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 Oversight — Search and list recent transactions or retrieve detailed metadata for specific payments.
Payment Lifecycle Management — Charge payment methods, capture authorized funds, void pending transactions, and issue full or partial refunds.
Customer Data Orchestration — Search your customer vault by email and retrieve detailed billing profiles and saved payment methods.
GraphQL Power — Leverage the flexibility of Braintree's modern GraphQL API for precise data retrieval.

The Braintree 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 Braintree to Pydantic AI via MCP

Follow these steps to integrate the Braintree 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 Braintree with type-safe schemas

Why Use Pydantic AI with the Braintree MCP Server

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

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

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

Braintree + Pydantic AI Use Cases

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

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

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

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

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

Braintree MCP Tools for Pydantic AI (8)

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

capture_transaction

Capture an authorized transaction

charge_payment_method

Charge a payment method

get_customer

Get details of a specific customer

get_transaction

Get details of a specific transaction

refund_transaction

Optionally provide a partial amount. Refund a settled transaction

search_customers

Search for customers

search_transactions

Search for recent transactions

void_transaction

Void an authorized transaction

Example Prompts for Braintree in Pydantic AI

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

"Search for recent transactions in Braintree."

"Find the customer profile for john@example.com."

"Refund $20.00 for transaction ID TX_NODE_123."

Troubleshooting Braintree MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Braintree + Pydantic AI FAQ

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