MCP Calculator Server

Integrations

  • Used for package management of the MCP Calculator Server, enabling installation of dependencies through commands like 'npm install' and running the server with 'npm run dev' or 'npm start'.

Servidor de calculadora MCP

A simple Model Context Protocol (MCP) server that provides calculator functions. ## Overview This MCP server implements basic arithmetic operations as tools that can be called by Large Language Models (LLMs) through the Model Context Protocol. ## Features - Addition: Add two numbers together - Subtraction: Subtract one number from another - Multiplication: Multiply two numbers together - Division: Divide one number by another (with validation to prevent division by zero) ## Installation ```bash npm install ``` ## Usage ### Running the server ```bash npm run dev ``` This starts the MCP server in development mode with auto-restart on file changes. For production: ```bash npm start ``` ### Testing with MCP Inspector You can test the server using the MCP Inspector: ```bash npx @modelcontextprotocol/inspector node src/index.js ``` This will open a web interface where you can: - View available tools - Test each calculator function with custom inputs - See the responses from the server ## Available Tools | Tool | Parameters | Description | |------|------------|-------------| | add | a: number, b: number | Adds two numbers | | subtract | a: number, b: number | Subtracts b from a | | multiply | a: number, b: number | Multiplies two numbers | | divide | a: number, b: number (non-zero) | Divides a by b | ## Example Usage When connected to an LLM through MCP, the model can call these tools to perform calculations. For example: - To add 5 and 3, the LLM would call the `add` tool with parameters `a: 5, b: 3` - To divide 10 by 2, the LLM would call the `divide` tool with parameters `a: 10, b: 2` ## License MIT

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Un servidor de protocolo de contexto de modelo simple que proporciona operaciones aritméticas básicas (suma, resta, multiplicación, división) como herramientas que pueden ser llamadas por modelos de lenguaje grandes.

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