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AEMET-MCP

AEMET-MCP

by AnCode666
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

find_nearby_stations

Locate weather stations near any geographic coordinate within a specified radius. Input latitude, longitude, and distance to get stations from AEMET.

Instructions

Find weather stations within a given radius (in km) from a given geographic coordinate.

Args: lat: Latitude in decimal degrees (e.g., 43.36) lon: Longitude in decimal degrees (e.g., -8.41) radio_km: Search radius in kilometers

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lat": "<lat>",
      "lon": "<lon>"
    },
    "name": "find_nearby_stations"
  }
}

Input Schema

NameRequiredDescriptionDefault
latYes
lonYes
radio_kmNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as whether results are sorted, any limits, how invalid coordinates are handled, or what the output looks like. The description is minimal.

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?

Description is very concise: one sentence plus a brief Args list. No extraneous information. Every line serves a purpose.

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 the lack of output schema and annotations, the description should provide more context. It doesn't describe what the tool returns (station IDs, names, coordinates?) or potential errors. Incomplete for an agent to fully understand usage.

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

Parameters3/5

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

Input schema properties have no descriptions (0% coverage). The description adds units (decimal degrees for lat/lon, km for radius) and examples for lat/lon, which is helpful. However, it does not specify valid ranges or constraints, so it is only partially compensatory.

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

Purpose5/5

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

Description explicitly states the tool finds weather stations within a radius from a coordinate. It uses a specific verb ('find') and resource ('weather stations'), and the radius and coordinate constraints are clear. This distinguishes it from sibling tools like get_station_list or get_station_data.

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 explicit guidance on when to use this vs alternatives. The agent must infer from tool names. No mention of when-not-to-use or prerequisites like requiring valid coordinates.

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

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