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ourairports-mcp-server

ourairports_find_airports
Read-onlyIdempotent

Find airports within a radius of a latitude/longitude, ranked nearest-first by great-circle distance, each with its distance (km) and bearing (degrees true) from the query point. The grounding tool for "nearest airport to here" — pair it with a live aviation server to fetch weather or positions for the result. Takes a coordinate only: no geocoding, so resolve place names to lat/lon upstream first (e.g. an OpenStreetMap or Open-Meteo geocode tool). Closed airports are excluded unless include_closed is set. OurAirports is community-edited — not authoritative for flight operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoRestrict to one airport type (e.g. large_airport for major fields only).
limitNoMaximum airports to return (1–50). Defaults to OURAIRPORTS_DEFAULT_SEARCH_LIMIT (20).
latitudeYesQuery point latitude in decimal degrees (WGS84), −90 to 90.
longitudeYesQuery point longitude in decimal degrees (WGS84), −180 to 180.
radius_kmNoSearch radius in kilometers (1–500). Defaults to 100.
include_closedNoInclude airports of type "closed". Off by default.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
noticeNoGuidance when no airport fell within the radius — e.g. widen radius_km.
airportsNoAirports within the radius, nearest-first.
totalCountNoNumber of airports returned within the radius.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description need not repeat those. It adds context beyond annotations by warning that 'OurAirports is community-edited — not authoritative for flight operations' and by disclosing that closed airports are excluded unless include_closed is set. No contradiction with annotations found.

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 compact, with the core purpose in the first sentence and supporting guidance (geocoding, data quality, include_closed) in the following three sentences. No redundant phrasing; every sentence earns its place. Information is front-loaded with the operative definition.

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?

Given the tool's moderate complexity (6 params, 2 required) and the presence of a complete output schema (not shown but declared), the description covers all essential aspects: what it does, how it ranks results, its distance/bearing output, prerequisites (geocoding), and a safety caveat about data authority. Nothing an agent needs to invoke it correctly is missing.

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?

Schema description coverage is 100% — every parameter (latitude, longitude, radius_km, type, limit, include_closed) has a clear description in the schema. The tool description adds no new parameter-specific meaning beyond what the schema already provides; it merely restates the coordinate requirement and the closed-airport default. Baseline 3 applies.

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 description states a precise operation: 'Find airports within a radius of a latitude/longitude, ranked nearest-first by great-circle distance.' It names the specific resource (airports), the geographic constraint, and the ranking order, clearly distinguishing this location-based lookup from siblings like ourairports_search_airports (text search) and ourairports_get_airport (by ID).

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?

The description explicitly states when to use this tool ('The grounding tool for "nearest airport to here"'), how to compose it with upstream geocoding ('no geocoding, so resolve place names to lat/lon upstream first'), and when to avoid it (not authoritative for flight operations). It also notes the optional include_closed flag to control scope.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct operation: spatial lookup (find_airports, find_navaids), code-based retrieval (get_airport), free-text/faceted search (search_airports), runway attribute search (search_runways), and a reference table (list_countries). No two tools overlap in purpose; even the two 'search' tools are clearly differentiated by entity type.

Naming Consistency5/5

All tool names follow a strict 'ourairports_<verb>_<noun>' pattern with snake_case throughout. Verbs are distinct and indicative (find, get, list, search), and nouns clearly identify the resource (airports, navaids, countries, runways). The pattern is uniform and predictable.

Tool Count5/5

The server exposes exactly 6 tools, which is well-scoped for its domain. Each tool addresses a distinct core need: spatial proximity, code resolution, text/facet search, runway attributes, navaid lookup, and country/region reference. No unnecessary tools, and the count is within the ideal 3-15 range.

Completeness5/5

The surface covers the full read-only lifecycle for aviation data: find by location, resolve by code, search by name/facets, inspect runways, and retrieve navaids. The inclusion of a country lookup table for valid filters and clear cross-references (e.g., search_airports → get_airport) demonstrates thoughtful coverage. Since the dataset is static, CRUD operations aren't expected, and no obvious gaps exist.