mcp-tung-shing is a Chinese Traditional Almanac (Tung Shing) calculation service based on the Model Context Protocol (MCP). It provides traditional calendar information such as auspicious/inauspicious times, suitable/unsuitable activities for specific dates and hours, including features like conversion between Gregorian and Lunar calendars, twelve double-hour periods, Five Elements, Gods, Stars, and more.
mcp-tung-shing helps users access detailed traditional Chinese calendar information, which can be used for planning events, understanding auspicious timings, and gaining insights into cultural practices. It supports both modern development workflows (via NPX or CLI) and integrates seamlessly with MCP configurations.
The repository is maintained by baranwang, who has contributed to its development and continues to manage updates and improvements.
The source code and documentation for mcp-tung-shing are hosted on GitHub under the repository baranwang/mcp-tung-shing.
The most recent commit in the repository was made on January 21, 2025, for files like tsconfig.json and vitest.config.ts.
You can integrate it using either the NPX method or CLI method. For NPX, add the relevant configuration block to your MCP settings with the command 'npx' and arguments '-y mcp-tung-shing'. For CLI, install the package globally via npm and reference 'mcp-tung-shing' directly in your MCP config.
The primary API endpoint is 'get-tung-shing', which accepts two parameters: 'startDate' (in YYYY-MM-DD format) and 'days' (number of days to retrieve, defaulting to 1).
No, mcp-tung-shing is specifically designed for calculating Chinese Traditional Almanac data, while VirusTotal MCP Server serves a different purpose related to malware scanning and analysis.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
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