# Skyscanner MCP Server — Claude, Cursor & AI Agents (`makework36/skyscanner-mcp-server`) Actor Plug-and-play Skyscanner MCP server for Claude Desktop, Cursor, Claude Code, ChatGPT and any MCP-compatible AI agent. Search flights with price, carrier, stops and duration in one tool call — no browser, no API key. - **URL**: https://apify.com/makework36/skyscanner-mcp-server.md - **Developed by:** [deusex machine](https://apify.com/makework36) (community) - **Categories:** AI, Integrations, Travel - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 tool calls This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Plug-and-play Skyscanner flight search as a native **Model Context Protocol** (MCP) server. Connect your AI agent (Claude Desktop, Cursor, Claude Code, ChatGPT, VS Code, Codex) and search flights in natural language. ### Connect from your MCP client MCP Standby endpoint: ```` https://makework36--skyscanner-mcp-server.apify.actor/mcp?token=YOUR\_APIFY\_TOKEN ```` #### Claude Desktop Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "skyscanner": { "url": "https://makework36--skyscanner-mcp-server.apify.actor/mcp?token=YOUR_APIFY_TOKEN" } } } ```` #### Cursor / Claude Code / VS Code Use the MCP configurator at [mcp.apify.com](https://mcp.apify.com) — select this Actor, click the install line for your client, paste and you're done. ### Available tools #### `search_flights` Search flights by origin/destination entity IDs and date(s). **Arguments:** | Name | Type | Required | Description | |------|------|----------|-------------| | `origin` | string | ✅ | Skyscanner entity ID (e.g. `27537542` for NYC) | | `destination` | string | ✅ | Entity ID or `"everywhere"` for cheapest-destination discovery | | `departDate` | string | ✅ | `YYYY-MM-DD` | | `returnDate` | string | — | `YYYY-MM-DD` for round-trip (omit for one-way) | | `adults` | integer | — | 1–9, default 1 | | `cabinClass` | enum | — | `economy`, `premium_economy`, `business`, `first` | | `market` | string | — | Two-letter market code (e.g. `US`, `GB`, `MX`) | | `currency` | string | — | ISO 4217 (default `USD`) | | `maxItineraries` | integer | — | 1–100, default 20 | **Returns:** JSON with the search summary + up to `maxItineraries` results (price, carriers, stops, duration, dep/arr times). ### Pricing **$0.05 per successful tool call.** Failed tool calls are not billed. ### How it works under the hood This MCP server wraps the battle-tested `makework36/skyscanner-flight-scraper-api` Actor. Each `search_flights` tool invocation: 1. Forwards arguments to the upstream scraper. 2. The scraper fetches fresh PerimeterX tokens from a dedicated token server. 3. Returns a curated JSON with the most relevant fields (compact for AI consumption). Full architecture documented in the companion Actor. ### Use cases for AI agents - **Travel assistants** that return cheapest options for a user query in natural language. - **Itinerary builders** that explore `destination=everywhere` to find surprise trips. - **Price-watch workflows** that schedule periodic `search_flights` and alert on drops. - **Business travel agents** that filter by `cabinClass=business` and carrier preferences. ### Model compatibility Tested with Claude Opus/Sonnet 4.x, GPT-4+, Cursor Agent mode, and the Apify `actors-mcp-server` auto-discovery. ### Related - [Airbnb MCP Server](https://apify.com/makework36/airbnb-mcp-server) — vacation rentals in the same style. - [Reddit MCP Server](https://apify.com/makework36/reddit-mcp-server) — 7 Reddit tools for agents. - Upstream scraper: [skyscanner-flight-scraper-api](https://apify.com/makework36/skyscanner-flight-scraper-api). # Actor input Schema ## `showSetupInstructions` (type: `boolean`): When enabled, the test run outputs MCP connection details (the Standby URL you paste in your AI client) and the full list of available flight-search tools — search\_flights — with their parameters, example args, and per-call pricing. Leave this enabled if you are exploring the Actor for the first time. This setting has no effect when the Actor is invoked via its Standby MCP endpoint from Claude, Cursor, or any other AI client. ## Actor input object example ```json { "showSetupInstructions": true } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("makework36/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 = {} # Run the Actor and wait for it to finish run = client.actor("makework36/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 '{}' | apify call makework36/skyscanner-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=makework36/skyscanner-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Skyscanner MCP Server — Claude, Cursor & AI Agents", "description": "Plug-and-play Skyscanner MCP server for Claude Desktop, Cursor, Claude Code, ChatGPT and any MCP-compatible AI agent. Search flights with price, carrier, stops and duration in one tool call — no browser, no API key.", "version": "1.0", "x-build-id": "SbfB3wuPoJQgxuLnC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/makework36~skyscanner-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-makework36-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/makework36~skyscanner-mcp-server/runs": { "post": { "operationId": "runs-sync-makework36-skyscanner-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/makework36~skyscanner-mcp-server/run-sync": { "post": { "operationId": "run-sync-makework36-skyscanner-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "showSetupInstructions": { "title": "Show setup instructions", "type": "boolean", "description": "When enabled, the test run outputs MCP connection details (the Standby URL you paste in your AI client) and the full list of available flight-search tools — search_flights — with their parameters, example args, and per-call pricing. Leave this enabled if you are exploring the Actor for the first time. This setting has no effect when the Actor is invoked via its Standby MCP endpoint from Claude, Cursor, or any other AI client.", "default": true } } }, "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 } } } } } } } } } } ```