Up Bank MCP Server

Name: Up Bank MCP Server
Author: stuliston

@stuliston

リポジトリ

Up Bank MCP Server について

MCP (Model Context Protocol) server implementation for Up Bank's API

基本情報

カテゴリ

金融とコマース

ライセンス

MIT license

ランタイム

python

トランスポート

stdio

公開者

stuliston

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": {
    "up-bank-mcp": {
      "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 Up Bank MCP Server?

An MCP (Model Context Protocol) server implementation for Up Bank's API, allowing AI agents to interact with Up Bank accounts. It provides account balance checking, transaction history viewing, and secure API token handling.

How to use Up Bank MCP Server?

Clone the repository, create a Python virtual environment (3.10+), install dependencies via pip install -r requirements.txt, and create a .env file with your Up Bank API token as UP_TOKEN. Then run the MCP server.

Key features of Up Bank MCP Server

Account balance checking
Transaction history viewing
Secure API token handling via .env
MCP‑compliant server implementation

Use cases of Up Bank MCP Server

AI agents retrieving current account balances
AI agents viewing recent transaction history
Integrating Up Bank data into MCP‑compatible tools

FAQ from Up Bank MCP Server

What does Up Bank MCP Server do?

It allows AI agents to interact with Up Bank accounts by providing account balance and transaction data through the Model Context Protocol.

What are the requirements?

Python 3.10 or later, a valid Up Bank API token, and the MCP SDK.

How do I set it up?

Clone the repository, create and activate a virtual environment, install dependencies from requirements.txt, and set your Up Bank API token in a .env file under UP_TOKEN.

How are API tokens handled?

Tokens are stored in a .env file, which is not committed to the repository, following Up Bank API security best practices.

Is the server production‑ready?

No, it is currently in the initial development phase with basic features being implemented.

「金融とコマース」の他のコンテンツ

AI看线 - A股技术分析与AI预测工具

QuantML-Github

Python-based stock analysis tool that combines traditional technical analysis with AI prediction capabilities. Providing comprehensive stock analysis and forecasting using K-line charts, technical indicators, financial data, and news data. With CMD/WEB/MCP supported.

333