# Skyscanner MCP Server (`axlymxp/skyscanner-mcp-server`) Actor MCP server exposing reliable Skyscanner place tools (entity resolution, Explore feed) for Claude, Cursor and AI agents. Token-only, no proxy. - **URL**: https://apify.com/axlymxp/skyscanner-mcp-server.md - **Developed by:** [axly](https://apify.com/axlymxp) (community) - **Categories:** Travel, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 dataset items This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Skyscanner MCP Server A **Model Context Protocol (MCP) server** that gives AI assistants — Claude, Cursor, ChatGPT, n8n, and custom agents — **Skyscanner place tools** as callable functions. Ask your assistant to resolve airports/cities or browse travel inspiration and it queries Skyscanner's own backend in real time. ### Who it's for - **AI-assistant users** who want to resolve places and browse destinations in chat. - **Agent/automation builders** (n8n, LangChain, custom) needing Skyscanner place tools. - **Travel apps** embedding conversational place lookup. - **Analysts** doing ad-hoc entity lookups without writing scraper code. ### Tools exposed | Tool | What it does | | ---------------------- | ---------------------------------------------------------------------------------------------------------- | | `resolve_entity` | Resolve a Skyscanner PlaceId / IATA code to its canonical travel entity (numeric id, type, country, names). | | `explore_destinations` | The Skyscanner "Explore" inspiration feed (featured destinations, promos). | Both tools work **out of the box with zero configuration** — anonymous token only, no proxy, no anti-bot handling. They run fast and consistently from any IP. ### Connect Run the Actor in **Standby** mode and point your MCP client at: ```` https:///mcp ```` (Streamable HTTP transport.) Example Claude Desktop / Cursor config: ```json { "mcpServers": { "skyscanner": { "url": "https:///mcp" } } } ```` Then ask: *"Resolve the Skyscanner entity for LHR"* or *"Show me the Skyscanner Explore destinations for the US market."* ### Example tool call ```json { "tool": "resolve_entity", "arguments": { "place_id": "LHR", "locale": "en-US" } } ``` Returns the entity `id`, `type` (City / Airport / Country), `countryCode` and localized names. ### Also runs as a classic run Provide `placeIds` (IATA codes / Skyscanner PlaceIds) in the input and run normally to push resolved entity rows to a dataset — handy for building a place reference table on a schedule. ### Reliability This server uses Skyscanner's entity and Explore services with an anonymous token — no proxy or anti-bot handling required, so tool calls are fast and consistent from any IP. ### FAQ **Does it return live flight prices?** No — this server exposes reliable place and Explore tools. Live fares sit behind Skyscanner's anti-bot and need a dedicated unblocker-backed scraper. **How fresh is the data?** Live at call time from Skyscanner's backend. **Do I need a proxy?** No — the exposed tools are token-only and work from any IP. **Is it legal?** You are responsible for complying with Skyscanner's terms and applicable law. Only publicly available place data is accessed. # Actor input Schema ## `placeIds` (type: `array`): Skyscanner PlaceIds or IATA codes to resolve to canonical travel entities. Only used when running the Actor as a one-shot run — leave empty for MCP Standby mode. ## `market` (type: `string`): Skyscanner market (2-letter). ## `locale` (type: `string`): Language-region locale. ## `currency` (type: `string`): 3-letter currency code. ## Actor input object example ```json { "placeIds": [ "LOND", "JFK", "NYCA" ], "market": "US", "locale": "en-US", "currency": "USD" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "placeIds": [ "LOND", "JFK", "NYCA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("axlymxp/skyscanner-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "placeIds": [ "LOND", "JFK", "NYCA", ] } # Run the Actor and wait for it to finish run = client.actor("axlymxp/skyscanner-mcp-server").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "placeIds": [ "LOND", "JFK", "NYCA" ] }' | apify call axlymxp/skyscanner-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=axlymxp/skyscanner-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Skyscanner MCP Server", "description": "MCP server exposing reliable Skyscanner place tools (entity resolution, Explore feed) for Claude, Cursor and AI agents. Token-only, no proxy.", "version": "0.1", "x-build-id": "F4ce6pigeuCE2JnOz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/axlymxp~skyscanner-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-axlymxp-skyscanner-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/axlymxp~skyscanner-mcp-server/runs": { "post": { "operationId": "runs-sync-axlymxp-skyscanner-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/axlymxp~skyscanner-mcp-server/run-sync": { "post": { "operationId": "run-sync-axlymxp-skyscanner-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "placeIds": { "title": "Place IDs / IATA codes (normal-run mode)", "type": "array", "description": "Skyscanner PlaceIds or IATA codes to resolve to canonical travel entities. Only used when running the Actor as a one-shot run — leave empty for MCP Standby mode.", "items": { "type": "string" } }, "market": { "title": "Market", "type": "string", "description": "Skyscanner market (2-letter).", "default": "US" }, "locale": { "title": "Locale", "type": "string", "description": "Language-region locale.", "default": "en-US" }, "currency": { "title": "Currency", "type": "string", "description": "3-letter currency code.", "default": "USD" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```