What dependencies does the server require?
Python 3.10 or higher and the uv package manager. Shioaji API credentials are also required.
@Sinotrade
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-shioaji": {
"command": "uv",
"args": [
"sync"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
MCP Server for Shioaji is a Model Context Protocol (MCP) server that gives AI assistants access to the Shioaji trading API for the Taiwanese financial market. It exposes Shioaji functionality as tools, allowing AI models to retrieve stock prices, fetch historical data, and scan stocks by ranking criteria.
Install with Python 3.10+ and the uv package manager (uv sync). Configure your Shioaji API credentials via environment variables (SHIOAJI_API_KEY, SHIOAJI_SECRET_KEY) or a .env file. Start the server with uv run mcp-server-shioaji; it listens on http://0.0.0.0:8000 by default.
Python 3.10 or higher and the uv package manager. Shioaji API credentials are also required.
Set the `SHIOAJI_API_KEY` and `SHIOAJI_SECRET_KEY` environment variables or provide them in a `.env` file in the server root directory.
The server does not store data locally; it fetches live data from the Shioaji API on each request.
The server runs as an HTTP server (default port 8000) and communicates via the Model Context Protocol (MCP).
The README does not specify rate limits, but it relies on the Shioaji API’s own constraints. The `scan_stocks` tool defaults to a limit of 20 results.
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