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ourairports-mcp-server

by io.github.cyanheads

ourairports-mcp-server

ourairports_get_airport
Read-onlyIdempotent

Fetch the full record for one airport resolved by ANY code — IATA (SEA), ICAO (KSEA), GPS, national/local, or the OurAirports ident — with its runways and radio frequencies inline. The single code param is resolved case-insensitively across all five identifier spaces (priority: ident, then ICAO, IATA, GPS, local). The response always echoes the airport's complete code set and a resolution_note naming which space matched, so a wrong resolution from an ambiguous national code is self-correcting (re-query with the IATA or ICAO code, or the ident). Absent codes are reported as null, never an error. Closed airports always resolve. OurAirports is community-edited — not authoritative for flight operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesAny airport code: IATA (SEA), ICAO (KSEA), GPS code, national/local code, or the OurAirports ident. Case-insensitive; surrounding whitespace is ignored.
includeNoWhich related records to include inline. Defaults to both. Pass a subset to trim the response.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
airportNoThe resolved airport record. Codes the airport lacks are null.
runwaysNoRunways for the airport. Empty when the airport has none OR when `runways` was not in `include` — check `included` to tell which.
includedNoWhich related-record sets this response carries, echoing the effective `include` selection. A relation NOT listed here was omitted by `include` (its array is empty for that reason); a listed relation with an empty array genuinely has no records.
frequenciesNoRadio frequencies in MHz. Empty when the airport has none OR when `frequencies` was not in `include` — check `included` to tell which.
resolvedViaNoWhich identifier space the code matched: ident, icao_code, iata_code, gps_code, or local_code.
resolutionNoteNoHuman-readable note on how the code resolved, including an ambiguity warning for shared national codes.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond readOnly and idempotent hints, it reveals case-insensitivity, resolution priority, response echoes, null handling, closed airport inclusion, and community-edited nature. No contradiction.

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?

Well-structured with core purpose first, followed by resolution details and caveats. No wasted sentences; all information is relevant and concise for its richness.

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 output schema exists and the description covers edge cases (ambiguous codes, nulls, closed airports, authoritative caveat), it is complete for an agent to call correctly.

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?

With 100% schema coverage, baseline is 3; description adds semantic detail for the code parameter (priority across five identifiers, whitespace ignored) and clarifies include default behavior. Adds value over 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?

States explicitly it fetches a full airport record by any code, specifying the verb and resource. It distinguishes from search tools by emphasizing resolution by code rather than search.

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

Usage Guidelines4/5

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

Provides guidance on resolution priority and self-correction for ambiguous codes, and notes behavior for closed airports. Does not explicitly contrast with search tools but context implies using this for known codes.

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.

Resources