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PayPal Credit MCP Server

@mourya317

Repository

About PayPal Credit MCP Server

No overview available yet

Basic information

Category

Finance & Commerce

Runtime

python

Transports

stdio

Publisher

mourya317

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is PayPal Credit MCP Server?

PayPal Credit MCP Server is an MCP (Model Context Protocol) wrapper that exposes PayPal Credit Risk APIs through a FastMCP interface. It enables AI agents and applications to evaluate credit approvability for customers via a standardized protocol. The server is designed for developers integrating PayPal credit services into AI‑driven workflows.

How to use PayPal Credit MCP Server?

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.

Key features of PayPal Credit MCP Server

  • 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

Use cases of PayPal Credit MCP Server

  • Enable an AI assistant to check customer credit eligibility in real time
  • Integrate PayPal credit decisions into automated onboarding workflows
  • Provide credit risk assessment inside conversational interfaces

FAQ from PayPal Credit MCP Server

What APIs does the server wrap?

It wraps the PayPal Credit Risk APIs, specifically the credit approvability evaluation endpoint.

How do I deploy the server?

Build the Docker image, push it to Google Container Registry, and deploy to Google Cloud Run. A deploy.sh script is provided after setting the PROJECT_ID.

What tools are available?

The server exposes one MCP tool: evaluate_credit_approvability – used to evaluate credit approvability for a customer.

What are the runtime requirements?

Python 3.9 or higher, Docker for containerization, and a Google Cloud project for deployment.

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