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What is An unofficial Model Context Protocol (MCP) server for interacting with PayPal Braintree payment processing services.?
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.
Documentation
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:
Configure claude_desktop_config.json to point to this server
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:
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
Clone this repository
git clone https://github.com/yourusername/braintree-mcp-server.git
cd braintree-mcp-server
Set up a Python 3.13+ environment
pyenv install 3.13.0
pyenv local 3.13.0
# Or using another method to ensure Python 3.13+
Install dependencies
pip install -e .
Configuration
Create a .env file in the project root with your Braintree credentials:
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
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
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.
response = await braintree_ping()\n\n# Returns "pong" if successful
braintree_execute_graphql
Execute arbitrary GraphQL queries against the Braintree API.
query = """
query GetTransactionDetails($id: ID!) {
node(id: $id) {
... on Transaction {
id
status
amount {
value
currencyCode
}
createdAt
}
}
}
"""
variables = {"id": "transaction_id_here"}
response = await braintree_execute_graphql(query, variables)\n\n# Returns JSON response from Braintree
Common GraphQL Operations# Fetch Customer
query GetCustomer($id: ID!) {
node(id: $id) {
... on Customer {
id
firstName
lastName
email
paymentMethods {
edges {
node {
id
details {
... on CreditCardDetails {
last4
expirationMonth
expirationYear
cardType
}
}
}
}
}
}
}
}
Create Transaction
mutation CreateTransaction($input: ChargePaymentMethodInput!) {
chargePaymentMethod(input: $input) {
transaction {
id
status
amount {
value
currencyCode
}
}
}
}