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  1. Home
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  3. Braintree MCP Server
  4. README

Braintree MCP Server README

The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Braintree MCP Server listing page.

Back to Braintree MCP Server View source on GitHub

Braintree MCP Server

An unofficial Model Context Protocol (MCP) server for interacting with PayPal Braintree payment processing services.

License and Citation

This project is available under the MIT License with an Academic Citation Requirement. This means you can freely use, modify, and distribute the code, but any academic or scientific publication that uses this software must provide appropriate attribution.

For academic/research use:

If you use this software in a research project that leads to a publication, presentation, or report, you must cite this work according to the format provided in CITATION.md.

For commercial/non-academic use:

Commercial and non-academic use follows the standard MIT License terms without the citation requirement.

By using this software, you agree to these terms. See LICENSE.md for the complete license text.

Server Versions

There are two versions of the Braintree MCP server available:

1. STDIO Transport Server (braintree_server.py)

  • Uses standard input/output (STDIO) for communication
  • Designed for integrations with Claude Desktop and other MCP clients that support STDIO
  • Each client session spawns a new server process
  • The server terminates when the client disconnects

Usage with Claude Desktop:

  1. Configure claude_desktop_config.json to point to this server
  2. Open Claude Desktop and select the Braintree tool

2. SSE Transport Server (braintree_sse_server.py)

  • Uses Server-Sent Events (SSE) for communication
  • Designed as a standalone web server that can handle multiple client connections
  • Server runs persistently until manually stopped
  • Binds to 127.0.0.1:8001 by default (configurable)

Manual Usage:

bash
python braintree_sse_server.py

Connecting to the SSE server: Use an MCP client that supports SSE transport and connect to http://127.0.0.1:8001/sse

Overview

This server implements the Model Context Protocol (MCP) specification to provide AI assistant models with direct, structured access to Braintree's payment processing capabilities via GraphQL API. It enables AI systems to perform payment operations like fetching transactions, creating payments, and managing customer data through MCP tools.

Installation

  1. Clone this repository
bash
git clone https://github.com/yourusername/braintree-mcp-server.git
cd braintree-mcp-server
  1. Set up a Python 3.13+ environment
bash
# If using pyenv
pyenv install 3.13.0
pyenv local 3.13.0

# Or using another method to ensure Python 3.13+
  1. Install dependencies
Terminal
pip install -e .

Configuration

Create a .env file in the project root with your Braintree credentials:

Code
BRAINTREE_MERCHANT_ID=your_merchant_id
BRAINTREE_PUBLIC_KEY=your_public_key
BRAINTREE_PRIVATE_KEY=your_private_key
BRAINTREE_ENVIRONMENT=sandbox  # or production

You can obtain these credentials from your Braintree Control Panel.

Usage

Running the server

Default STDIO Transport

bash
python braintree_server.py

The server runs using stdio transport by default, which is suitable for integration with AI assistant systems that support MCP.

Server-Sent Events (SSE) Transport

bash
python braintree_sse_server.py

The SSE server provides a web-based transport layer that allows multiple persistent client connections. This is useful for standalone deployments where multiple clients need to access the Braintree functionality.

Default configuration:

  • Host: 127.0.0.1 (localhost)
  • Port: 8001
  • Environment: Defined in your .env file

See requirements.txt for the required dependencies.

Available MCP Tools

braintree_ping

Simple connectivity test to check if your Braintree credentials are working.

python
response = await braintree_ping()
# Returns "pong" if successful

braintree_execute_graphql

Execute arbitrary GraphQL queries against the Braintree API.

python
query = """
query GetTransactionDetails($id: ID!) {
  node(id: $id) {
    ... on Transaction {
      id
      status
      amount {
        value
        currencyCode
      }
      createdAt
    }
  }
}
"""

variables = {"id": "transaction_id_here"}

response = await braintree_execute_graphql(query, variables)
# Returns JSON response from Braintree

Common GraphQL Operations

Fetch Customer

graphql
query GetCustomer($id: ID!) {
  node(id: $id) {
    ... on Customer {
      id
      firstName
      lastName
      email
      paymentMethods {
        edges {
          node {
            id
            details {
              ... on CreditCardDetails {
                last4
                expirationMonth
                expirationYear
                cardType
              }
            }
          }
        }
      }
    }
  }
}

Create Transaction

graphql
mutation CreateTransaction($input: ChargePaymentMethodInput!) {
  chargePaymentMethod(input: $input) {
    transaction {
      id
      status
      amount {
        value
        currencyCode
      }
    }
  }
}

With variables:

config.json
{
  "input": {
    "paymentMethodId": "payment_method_id_here",
    "transaction": {
      "amount": "10.00",
      "orderId": "order123",
      "options": {
        "submitForSettlement": true
      }
    }
  }
}

Troubleshooting

  • Ensure your Braintree credentials are correct in the .env file
  • Verify your network connection can reach Braintree's API endpoints
  • Check for any rate limiting or permission issues with your Braintree account