PayPal Credit MCP Server

by mourya317

161 downloads
Not rated
GitHub

Description

# PayPal Credit MCP Server This project provides an MCP wrapper around PayPal Credit Risk APIs. ## Features - Evaluate credit approvability ## Development ### Prerequisites - Python 3.9+ - Docker (for containerization) ### Setup 1. Clone the repository: ```bash git clone…

About

# PayPal Credit MCP Server This project provides an MCP wrapper around PayPal Credit Risk APIs. ## Features - Evaluate credit approvability ## Development ### Prerequisites - Python 3.9+ - Docker (for containerization) ### Setup 1. Clone the repository: ```bash git clone <repository-url> cd credit-risk-mcp-server ```…

Details

Author
mourya317
Downloads
161
Categories
Finance

- Wraps PayPal Credit Risk APIs as MCP tools
- Single tool: evaluate_credit_approvability
- Deployable to Google Cloud Run via Docker
- Built with FastMCP for MCP compliance
- Python 3.9+ and Docker required

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name PayPal Credit MCP Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

The server is deployed to Google Cloud Run using Docker. After deployment, you access the FastMCP server via the Cloud Run URL. The only exposed tool is evaluate_credit_approvability, which you invoke through the MCP interface to check a customer’s credit eligibility.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "paypal credit mcp server": {
            "credit-risk-mcp-server": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

McpServers

{
    "credit-risk-mcp-server": {
        "command": "python",
        "args": [
            "-m",
            "venv",
            "venv"
        ]
    }
}

PayPal Credit MCP Server

This project provides an MCP wrapper around PayPal Credit Risk APIs.

Features

- Evaluate credit approvability

Development

Prerequisites

- Python 3.9+
- Docker (for containerization)

Setup

1. Clone the repository:

   git clone <repository-url>
cd credit-risk-mcp-server

2. Install dependencies:
It is recommended to use a virtual environment:

   python -m venv venv
source venv/bin/activate # On Windows use venv\Scripts\activate
pip install -r requirements.txt

3. Run the application locally:

   python src/main.py

Deployment

To deploy the application to Google Cloud Run, follow these steps:

1. Build the Docker image:

   docker build -t gcr.io/<your-project-id>/credit-risk-mcp-server .

2. Push the Docker image to Google Container Registry:

   docker push gcr.io/<your-project-id>/credit-risk-mcp-server

3. Deploy to Google Cloud Run:

   gcloud run deploy credit-risk-mcp-server \
--image gcr.io/<your-project-id>/credit-risk-mcp-server \
--platform managed \
--region <your-region> \
--allow-unauthenticated

Or simply use the provided deployment script:

   ./deploy.sh

(Make sure to update the PROJECT_ID in the script first)

Usage

Once deployed, you can access the FastMCP server via the URL provided by Google Cloud Run. You can use the endpoints to access PayPal Credit services through the Machine Conversation Protocol interface.

Available Tools

Credit Risk API

- evaluate_credit_approvability - Evaluate credit approvability for a customer

Testing

Run the tests using pytest:

pytest src/tests/

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any enhancements or bug fixes.

No reviews yet — be the first

Sign in to leave a review

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.