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ourairports-mcp-server

by io.github.cyanheads

ourairports-mcp-server

ourairports_search_airports
Read-onlyIdempotent

Search the bundled OurAirports corpus by free-text (name / municipality / keywords) and/or facets (country, region, type). Every query token must match (word order and partial words are handled). Returns ranked airport summaries — operational and larger airports first — each with its full code set and coordinates, ready to chain into ourairports_get_airport. Closed airports are excluded unless include_closed is set. Use ourairports_list_countries for valid country/region codes. For "nearest airport to a coordinate" use ourairports_find_airports instead. OurAirports is community-edited — not authoritative for flight operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoRestrict to one airport type: large_airport, medium_airport, small_airport, heliport, seaplane_base, balloonport, or closed.
limitNoMaximum airports to return (1–100). Defaults to OURAIRPORTS_DEFAULT_SEARCH_LIMIT (20).
queryNoFree-text search over airport name, municipality, and keywords. Tokens are AND-matched. Omit to browse purely by facets.
regionNoISO 3166-2 region code filter (e.g. US-WA). Exact match, case-insensitive; surrounding whitespace is ignored.
countryNoISO 3166-1 alpha-2 country code filter (e.g. US). Exact match, case-insensitive; surrounding whitespace is ignored. Discover codes with ourairports_list_countries.
include_closedNoInclude airports of type "closed". Off by default — closed airports pollute the live-flight grounding use case.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
capNoThe limit that was applied. Present only when results were truncated.
errorNoPresent when the call failed. Absent on success.
shownNoNumber of airports returned. Present only when results were truncated.
noticeNoGuidance when nothing matched or results were capped — how to broaden or narrow.
airportsNoMatching airports, ranked best-first. Codes the airport lacks are null.
truncatedNoPresent and true only when more airports matched than were returned.
totalCountNoTotal airports matched before the limit was applied.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover read-only and idempotent; description adds matching rules (every token must match), ranking (operational and larger first), and the caveat that data is community-edited. Also states return fields (full code set, coordinates) and exclusion behavior. This goes beyond annotations to inform agent behavior.

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 front-loads the core purpose and keeps every sentence functional. It avoids fluff and packs usage guidance, caveats, and sibling routing into a compact paragraph.

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?

For a read-only search tool with an output schema, the description covers usage, parameter semantics, alternatives, and data caveats. It also mentions chaining into get_airport and list_countries for codes. Nothing an agent needs to invoke 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 coverage is 100%, so each parameter has a description. The tool description restates the query semantics (tokens AND-matched) and facet filters but doesn't add meaning significantly beyond what the schema already provides. Baseline 3 is appropriate.

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 a specific verb (search) + resource (OurAirports corpus) and the facets (country, region, type). Distinguishes from siblings by naming ourairports_find_airports for nearest-coordinate and ourairports_get_airport for chaining. Clear and specific.

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?

Explicitly says when to use this tool vs alternatives: 'For nearest airport to a coordinate use ourairports_find_airports instead' and 'Use ourairports_list_countries for valid country/region codes'. Also clarifies that closed airports are excluded unless include_closed, and that query tokens are AND-matched. No ambiguity.

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.

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