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🌐 MCP para todo – Servidor modular con herramientas útiles

@elsantiwg

Repository

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

Basic information

Category

Productivity

Runtime

node

Transports

stdio

Publisher

elsantiwg

Config

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

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

Tools

No tools detected

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.

FAQ from 🌐 MCP para todo

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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