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Buienradar MCP Server

Buienradar MCP Server

by wpnbos
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Servidor MCP de Buienradar

insignia de herrería

Descripción general

Este es un servidor MCP que obtiene datos de precipitación para una latitud y longitud determinadas mediante Buienradar. Ofrece una única herramienta MCP, get_precipitation_for , que proporciona pronósticos de precipitación para las próximas dos horas.

Instalación mediante herrería

Para instalar Buienradar MCP Server para Claude Desktop automáticamente a través de Smithery :

npx -y @smithery/cli install @wpnbos/buienradar-mcp-server --client claude

Related MCP server: Buienradar MCP Server

Configuración

Primero, asegúrese de tener uv (y Python) instalado.

Para integrar este servidor con Claude for Desktop , actualice su archivo de configuración en:

MacOS/Linux

~/Library/Application Support/Claude/claude_desktop_config.json

Ventanas

code $env:AppData\Claude\claude_desktop_config.json

Ejemplo de configuración:

{
    "mcpServers": {
        "precipitation": {
            "command": "uv",
            "args": [
                "--directory",
                "/ABSOLUTE/PATH/TO/PARENT/FOLDER/buienradar-mcp-server",
                "run",
                "server.py"
            ]
        }
    }
}

Reemplace /ABSOLUTE/PATH/TO/PARENT/FOLDER/buienradar-mcp-server con la ruta real donde se encuentra su servidor.

Reinicie Claude for Desktop para que la herramienta esté disponible.

Es posible que deba proporcionar la ruta completa de uv en lugar de solo uv . Para encontrar la ruta completa de su ejecutable uv , en macOS/Linux, ejecute which uv .

Uso

Si todo salió bien, deberías poder preguntarle a Claude sobre cualquier precipitación próxima.

> Will there be any rain soon in Amsterdam?

> No rain predicted in Amsterdam for the next 2 hours.

Available Tools

1 tool
get_precipitation_forC

Fetches precipitation data for the next 2 hours from Buienradar.

NameRequiredDescriptionDefault
latYes
lonYes

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states it fetches data without disclosing behavioral traits like rate limits, authentication needs, data freshness, error conditions, or response format. It mentions the source (Buienradar) but not what that implies for reliability or availability.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste—it directly states the tool's function, time scope, and data source. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on parameters, return values, error handling, and operational constraints, which are critical for a data-fetching tool with required inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides no information about the parameters (lat, lon). It doesn't explain what these represent (latitude/longitude coordinates), valid ranges, units, or how they affect the data fetched, leaving parameters completely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('fetches precipitation data') and resource ('from Buienradar'), with specific time scope ('for the next 2 hours'). It doesn't need to differentiate from siblings since none exist, but could be more specific about what precipitation data includes (e.g., rainfall intensity, probability).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives or prerequisites. The description mentions the data source (Buienradar) but doesn't explain limitations or appropriate contexts for use, leaving the agent without operational context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedget_precipitation_for
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The naming follows a clear verb_noun pattern (get_precipitation_for).

Tool Count2/5

One tool is too few for a weather data server, as it severely limits functionality. A Buienradar server should ideally include tools for forecasts, radar images, or location-based queries, making this set incomplete and under-scoped.

Completeness1/5

The tool set is severely incomplete for a weather data domain. It only provides precipitation data for a short timeframe, with no coverage for forecasts, historical data, radar visuals, or other essential weather parameters, leading to significant gaps in functionality.

Maintenance

ActivityInactive
ResponsivenessNo issues

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