PayPal Credit MCP Server

Name: PayPal Credit MCP Server
Author: mourya317

@mourya317

リポジトリ

PayPal Credit MCP Server について

概要はまだありません

基本情報

カテゴリ

金融とコマース

ランタイム

python

トランスポート

stdio

公開者

mourya317

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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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