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SoapyRED

FreightUtils MCP Server

nearest_airport

Read-onlyIdempotent

Find the closest airports to any latitude/longitude, sorted by distance with distance in kilometers. Optionally filter by type or radius.

Instructions

Find the airports nearest to a caller-provided latitude/longitude, sorted by great-circle (haversine) distance with distance_km on each result. Inputs: latitude, longitude (required), optional radius_km, max_results (1-50, default 10) and type filter (e.g. large_airport only). Coordinates are INPUT only — nothing is stored or logged. Searches 85,555 airports (OurAirports, public domain). Use when an agent already holds a coordinate (a port, warehouse, city centre, or the user's location) and needs the closest airport(s). This tool does NOT geocode place names and does NOT compute routes — pass coordinates you already have. Distinct from airport_lookup (exact code / name lookup, no distance) and unlocode_lookup (named transport-location search).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional filter by airport type
latitudeYesLatitude in decimal degrees (-90 to 90)
longitudeYesLongitude in decimal degrees (-180 to 180)
radius_kmNoOptional maximum distance in kilometres
max_resultsNoMax results to return (1-50, default 10)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaNo
countYes
_sourceYes
resultsYes
disclaimerYes
Behavior5/5

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

Discloses that coordinates are input only, nothing stored/logged, uses haversine distance, and references public dataset size. No contradiction with annotations.

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?

Concise yet comprehensive; important info front-loaded. Every sentence adds value without redundancy.

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

Completeness5/5

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

With output schema present, the description covers purpose, usage, exclusions, parameter details, and behavioral transparency fully.

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

Parameters4/5

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

Schema covers 100% of parameters with descriptions. Description adds default value for max_results (10) and example for type filter, adding value beyond schema.

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?

The first sentence clearly states the tool finds nearest airports to given coordinates sorted by haversine distance. It distinguishes from sibling tools airport_lookup and unlocode_lookup.

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

Usage Guidelines5/5

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

Provides explicit guidance: use when agent has coordinates, does not geocode or compute routes, and names specific alternatives for different needs.

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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