Kr MCP Server Overview

Kr MCP Server is a lightweight, Go‑based implementation of the Model Context Protocol (MCP) that bundles a set of ready‑to‑use tools for AI assistants. Its primary purpose is to give developers a quick, extensible way to expose external APIs—such as weather data and game currency queries—to AI agents without writing custom integrations. By leveraging the MCP‑Go framework, the server automatically registers resources, tools, and prompts, allowing Claude or other MCP‑compatible assistants to discover and invoke them through a single endpoint.

The server solves the common pain point of integrating third‑party services into conversational AI workflows. Instead of having an assistant send raw HTTP requests, developers can define a tool once and let the AI call it by name. For example, a user might ask, “What’s the weather in Beijing tomorrow?” and the assistant will forward that request to the server, which in turn calls the Juhe weather API and returns a concise, AI‑friendly response. This pattern keeps the agent’s logic clean while delegating domain knowledge to specialized services.

Key capabilities of Kr MCP Server include:

• Weather Query Tool – Fetches current or forecasted weather from the Juhe data API, requiring only an API key set via environment variable.
• DNF Gold Query Tool – Retrieves in‑game currency information for the popular MMORPG DNF, enabling game‑related assistance.
• Server‑Sent Events (SSE) – Supports real‑time event streams, allowing the server to push updates or notifications directly to connected clients.
• Resource & Prompt Support – Exposes additional metadata and custom prompts that an assistant can use to tailor responses or clarify user intent.
• Extensibility – New tools and prompts can be added by creating simple Go modules under the directory, automatically picked up by MCP‑Go.

Real‑world use cases span from customer support bots that need to provide weather alerts, to gaming assistants that keep players informed about in‑game economies. In a corporate setting, the same architecture can be extended to query internal APIs—such as inventory levels or employee directories—without exposing those services directly to the AI. The server’s SSE capability also opens possibilities for live dashboards or notification systems that react instantly to changes in external data sources.

By abstracting API calls into MCP tools, Kr MCP Server gives developers a modular, secure, and maintainable bridge between AI assistants and external data. Its minimal footprint, clear documentation, and open‑source MIT license make it an attractive starting point for any team looking to enrich their AI workflows with real‑world information.