citiesLook up cities and their primary airport from the Aviationstack database by free-text name, IATA city code (e.g. NYC), or ISO country code.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| search | No | ||
| iata_code | No | City IATA code (e.g. "NYC" for all NYC airports) | |
| country_iso2 | No |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | Array of city objects | |
| pagination | No | Pagination metadata |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / properties / data / items / properties / geoname_idAdded value: +{
+ "description": "GeoNames identifier; null for ~37% of cities",
+ "type": [
+ "string",
+ "null"
+ ]
+}Output schema / properties / data / items / properties / gmt / descriptionPrevious value: -"GMT offset"New value: +"GMT offset; null for some cities"Output schema / properties / data / items / properties / gmt / typePrevious value: -"string"New value: +[
+ "string",
+ "null"
+]Output schema / properties / data / items / properties / latitude / descriptionPrevious value: -"Latitude coordinate"New value: +"Latitude coordinate (aviationstack returns it as a string)"Output schema / properties / data / items / properties / latitude / typePrevious value: -"number"New value: +"string"Output schema / properties / data / items / properties / longitude / descriptionPrevious value: -"Longitude coordinate"New value: +"Longitude coordinate (aviationstack returns it as a string)"Output schema / properties / data / items / properties / longitude / typePrevious value: -"number"New value: +"string"Input schema / examplesAdded value: +[
+ {
+ "iata_code": "NYC"
+ },
+ {
+ "country_iso2": "FR",
+ "search": "Paris"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "data": {
+ "description": "Array of city objects",
+ "items": {
+ "properties": {
+ "city_name": {
+ "description": "City name",
+ "type": "string"
+ },
+ "country_iso2": {
+ "description": "Country ISO code",
+ "type": "string"
+ },
+ "country_name": {
+ "description": "Country name",
+ "type": "string"
+ },
+ "gmt": {
+ "description": "GMT offset",
+ "type": "string"
+ },
+ "gmt_offset_seconds": {
+ "description": "GMT offset in seconds",
+ "type": "number"
+ },
+ "iata_code": {
+ "description": "City IATA code",
+ "type": "string"
+ },
+ "latitude": {
+ "description": "Latitude coordinate",
+ "type": "number"
+ },
+ "longitude": {
+ "description": "Longitude coordinate",
+ "type": "number"
+ },
+ "timezone": {
+ "description": "IANA timezone",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "pagination": {
+ "description": "Pagination metadata",
+ "properties": {
+ "count": {
+ "type": "number"
+ },
+ "limit": {
+ "type": "number"
+ },
+ "offset": {
+ "type": "number"
+ }
+ },
+ "type": "object"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the data source and the 'primary airport' scope, but does not disclose behaviors like default limit, pagination, or how multiple parameters interact. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that wastes no words. It efficiently conveys the tool's purpose, data source, and all lookup methods without filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and the tool's relative simplicity, the description is mostly complete. It does not explain optionality of parameters or the effect of combining them, but the schema examples partially cover that. Minor gaps remain around default behavior when no parameters are supplied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (only iata_code is described), so the description must compensate. The text explains that 'search' is free-text name, 'iata_code' is a city IATA code, and 'country_iso2' is an ISO country code, adding meaning beyond the schema. The 'limit' parameter is not mentioned, but its role as a number is inferable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('look up'), a specific resource ('cities and their primary airport'), and the data source ('Aviationstack database'). It also distinguishes this tool from siblings like 'airports' and 'countries' by focusing on city-level lookups with primary airport info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context by specifying the three lookup modes: free-text name, IATA city code, and ISO country code. However, it does not explicitly mention when to prefer this tool over alternatives like 'airports' or provide exclusion criteria, so it stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, and deep_research all routing queries, and the polymarket family (arbitrage, edges, edge_tracker, fill_risk) covering similar ground. While descriptions are detailed, an agent could easily select the wrong tool.
Tool names mix bare nouns (airlines, airports, flights) with verb phrases (compare_entities, resolve_entity) and standalone verbs (remember, forget), with no consistent verb_noun pattern. Names like ask_pipeworx_beta and scan_competitor_ai_presence are internally inconsistent with the rest.
37 tools is far beyond the typical scope for a single server, and many are unrelated to the aviation theme, suggesting a lack of focus. The core aviation functionality only accounts for 6 of the tools.
The aviation tools (airlines, airports, flights, routes, cities, countries) cover basic lookups, but advanced operations like delay statistics or aircraft data are absent. The unrelated tools do not fill these gaps, and the overall surface feels shallow for a server claiming to be an Aviationstack.