MCP para todo – Servidor modular con herramientas útiles

@elsantiwg

Basic information

About MCP para todo – Servidor modular con herramientas útiles

🌐 Servidor MCP (Model Context Protocol) con herramientas útiles. Conecta LLMs con APIs reales: clima, cálculos, diccionario y más. TypeScript + Node.js.

#mcpe #mcp #mcp-server

MCP para todo – Servidor modular con herramientas útiles config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "MCP-para-todo": {
      "command": "node",
      "args": [
        "--version",
        "#",
        "≥",
        "18.0.0"
      ]
    }
  }
}

MCP para todo – Servidor modular con herramientas útiles tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is 🌐 MCP para todo?

It is an educational MCP (Model Context Protocol) server that connects language models like ChatGPT with external tools in real time. Built in TypeScript with a modular, extensible architecture, it implements three built‑in tools: weather lookup, word definitions, and math evaluation.

How to use 🌐 MCP para todo?

Clone the repository, run npm install, copy .env.example to .env, and add your API keys for OpenWeather and DictionaryAPI. Start the server with npm run dev. Any MCP‑compatible client can then call the tools (e.g., get_weather, word_definition, evaluate_math) via WebSocket.

Key features of 🌐 MCP para todo

Three pre‑built tools: get_weather, word_definition, evaluate_math.
Integrates with OpenWeather and DictionaryAPI.
Modular design for easy addition of new tools.
Compatible with any client that implements the MCP standard.
Written in TypeScript 5.0+ and runs on Node.js 18+.

Use cases of 🌐 MCP para todo

Smart assistants that answer weather, definitions, or math queries in real time.
Customer service bots with access to live data.
Personal assistants that combine conversation with external information.
Automation pipelines that offload calculations or dictionary lookups to an LLM.
Business systems that embed AI reasoning with real‑world data.

Frequently asked questions

What runtime is required?

Node.js 18+ and npm 9+.

How do I configure the server?

Copy `.env.example` to `.env` and fill in your `OPENWEATHER_API_KEY` and optionally the `DICTIONARY_API_URL`.

What transport protocol does the server use?

The connection example uses WebSocket (`ws://localhost:3000`).

How can I add a new tool?

Create a handler file in `src/tools/` following the `ToolHandler` interface, then register it in `src/tools/index.ts`.

Is authentication required?

External API keys are used for weather and dictionary services; no built

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