MCP Server Tutorial

@cthuaung

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

cthuaung

关于 MCP Server Tutorial

暂无概览

#mathgpt #math-solver #math-assistant

MCP Server Tutorial 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "MCP Server Tutorial": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

MCP Server Tutorial 工具

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。

概览

What is MCP Server Tutorial?

MCP Server Tutorial is a simple MCP (Model Context Protocol) server built with FastMCP that provides various mathematical operations as tools and a dynamic greeting resource. It is intended for developers learning to create and use MCP servers.

How to use MCP Server Tutorial?

Install Python 3.8+, create a virtual environment, and install FastMCP. Run the server with python main.py using SSE transport by default. Connect via MCP Inspector (run npx @modelcontextprotocol/inspector, choose SSE, and connect to http://localhost:8000/sse).

Features of MCP Server Tutorial

Basic arithmetic: addition, subtraction, multiplication, division
Advanced math: power, square root, cube root, factorial, logarithm, trigonometry
Dynamic greeting resource (greeting://{name})
Supports SSE and stdio transport protocols
Easily extensible with @mcp.tool() and @mcp.resource() decorators

Use cases of MCP Server Tutorial

Learning how to build and run an MCP server with FastMCP
Prototyping mathematical tool integrations in AI assistants
Demonstrating SSE-based MCP connections via Inspector

常见问题

What are the prerequisites for running this server?

Python 3.8 or higher and the FastMCP library. Dependencies are installed via `uv install fastmcp`.

Which transport protocols are supported?

FastMCP supports two transport protocols: `stdio` (terminal-based) and `sse` (Server-Sent Events, browser-based compatible with MCP Inspector). The default is SSE.

How can I add new tools or resources?

Add a new tool by using the `@mcp.tool()` decorator or a new resource by using the `@mcp.resource()` decorator in `main.py`.

Where does the server’s data live?

No external databases or storage are mentioned; all operations are stateless calculations performed in memory.

Is authentication or authorization required?

The README does not mention any authentication or authorization mechanisms.

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