MCP Weather Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Weather Serverwhat's the forecast for Barcelona this weekend?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Introducción a los MCP
En este proyecto se han seguido los pasos del vídeo de Midudev: https://www.youtube.com/watch?v=wnHczxwukYY junto con otra documentación educativa para aprender sobre los MCP (Model Context Protocol) y crear mi primer MCP.
Descripción
Se han hecho pruebas con Claude para comprobar el funcionamiento de los MCP con los archivos de mi equipo y una base de datos postgress junto con la creación de un MCP personalizado.
Herramientas/tecnologías utilizadas:
Node.js
pnpm
Visual Studio Code
Claude
@modelcontextprotocol/sdk (https://github.com/modelcontextprotocol/modelcontextprotocol)
zod
tsx
Related MCP server: My MCP Server
Creación del proyecto
mkdir mcp-weather
cd mcp-weather
pnpm init # Creará el package.jsonA partir de este punto quedaría crear el archivo main.ts y seguir los pasos del video.
Dependencias
pnpm add @modelcontextprotocol/sdk zod
pnpm add -D tsxEstructura del proyecto
main.ts: Código fuente del servidor MCP.package.json: Dependencias y scripts del proyecto..gitignore: Archivos y carpetas ignorados por git.pnpm-lock.yaml: Archivo de bloqueo de dependencias (ignorado en git).README.md: Documentación del proyecto.
Available Tools
1 toolfetch-weatherC
Tool to fetch the weather of a city
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | Nombre de la ciudad |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It doesn't describe response format, error handling, rate limits, authentication needs, or other behavioral traits beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single, direct sentence that clearly states the tool's purpose. There is no wasted verbiage, and it is appropriately front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for effective tool use. It doesn't explain what weather data is returned, format details, or other contextual information needed beyond the basic action, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'city' parameter documented as 'Nombre de la ciudad'. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('fetch') and resource ('weather of a city'), making it immediately understandable. However, it doesn't differentiate from siblings since there are none, so it can't achieve the highest score for that criterion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or context-specific considerations. It merely states what the tool does without any usage instructions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'fetch-weather' has a clearly distinct and unambiguous purpose.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'fetch-weather' follows a clear verb-noun pattern.
A single tool is too few for a weather server's apparent scope, which typically involves multiple operations like forecasts, alerts, or historical data. This minimal set feels thin and incomplete for the domain.
The tool surface is severely incomplete for a weather domain. It only provides current weather for a city, missing essential operations like forecasts, alerts, multi-location queries, or historical data, which will cause agent failures in broader tasks.
Maintenance
Resources
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