# Priceline Travel MCP Server (`axlymxp/priceline-travel-mcp-server`) Actor MCP server + scraper for Priceline. Search hotels and flights, and fetch hotel details and guest reviews live from Claude, ChatGPT, Cursor and other AI agents — or run it as a classic Priceline hotel scraper. Pay per tool call. - **URL**: https://apify.com/axlymxp/priceline-travel-mcp-server.md - **Developed by:** [axly](https://apify.com/axlymxp) (community) - **Categories:** Travel, AI, Automation - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 dataset items 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/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 ## Priceline Travel MCP Server Give your AI assistant **live access to Priceline** hotels and flights. This actor runs as a **Model Context Protocol (MCP) server** — connect Claude, ChatGPT, Cursor or any MCP-capable agent and it can search hotels, pull hotel details and reviews, and get flexible-date flight fares on demand. It also works as a classic one-shot Priceline hotel scraper. ### Who it's for - **AI-assistant users** — ask "find 4-star hotels in Miami under $200 for next weekend" and get live answers inside your chat. - **Agent & app builders** — add real Priceline travel data to an LLM app without writing or maintaining a scraper. - **Analysts** — pull hotels or fares interactively while researching a market. ### MCP tools | Tool | What it does | | -------------------------- | ----------------------------------------------------------------- | | `autocomplete_destination` | Resolve a place name to Priceline destinations + geo ids | | `search_hotels` | Search hotels by destination + dates (prices, ratings, amenities) | | `get_hotel_details` | Rooms, rates and highlights for one hotel | | `get_hotel_reviews` | Guest reviews for a hotel | | `flight_fare_matrix` | Flexible-date flight fare matrix (cheapest per date) | ### Connect it (Standby mode) 1. Start the actor in **Standby** mode on Apify. 2. Point your MCP client at `/mcp` (Streamable HTTP transport). 3. The tools above appear automatically in your assistant. Example (Claude Desktop / Cursor MCP config): ```json { "mcpServers": { "priceline": { "url": "https:///mcp" } } } ```` ### Classic scraper mode Prefer a dataset? Run it normally with input like: ```json { "destination": "New York", "checkIn": "2026-09-01", "checkOut": "2026-09-03", "sort": "PRICE", "limit": 50 } ``` It pushes one row per hotel (name, star level, price, rating, amenities, geo) to the dataset — the same fields as the Priceline Hotel Scraper. ### Example tool result ```json { "destination": "Miami", "count": 2, "hotels": [ { "hotel_id": "3356003", "name": "Super 8 by Wyndham Florida City", "star_level": "2.5-Star Hotel", "price_amount": "44.25", "price_currency": "USD", "review_count_label": "1,002 Reviews" } ] } ``` ### FAQ **Which assistants work?** Any MCP client — Claude Desktop, Cursor, Windsurf, or your own agent using the MCP SDK. **How fresh is the data?** Live — every tool call queries Priceline in real time. **Do I need an API key from Priceline?** No. The actor handles access for you. **Can I still get a dataset?** Yes — run it in normal mode with a `destination`. **Is this legal?** The actor accesses publicly available travel data. You are responsible for using it in line with applicable laws and Priceline's terms. # Actor input Schema ## `destination` (type: `string`): City name (auto-resolved) or numeric Priceline geo id. Required only for classic (non-MCP) scraping runs. ## `checkIn` (type: `string`): Check-in YYYY-MM-DD (classic run). Defaults to 30 days from today. ## `checkOut` (type: `string`): Check-out YYYY-MM-DD (classic run). Defaults to 32 days from today. ## `sort` (type: `string`): How to sort classic-run results. ## `limit` (type: `integer`): Maximum number of hotels to retrieve in a classic run. ## Actor input object example ```json { "destination": "New York", "checkIn": "2026-09-01", "checkOut": "2026-09-03", "sort": "RECOMMENDED", "limit": 50 } ``` # 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("axlymxp/priceline-travel-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("axlymxp/priceline-travel-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 axlymxp/priceline-travel-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=axlymxp/priceline-travel-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Priceline Travel MCP Server", "description": "MCP server + scraper for Priceline. Search hotels and flights, and fetch hotel details and guest reviews live from Claude, ChatGPT, Cursor and other AI agents — or run it as a classic Priceline hotel scraper. Pay per tool call.", "version": "1.0", "x-build-id": "IIHUnbpikaz7X8Qwn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/axlymxp~priceline-travel-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-axlymxp-priceline-travel-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/axlymxp~priceline-travel-mcp-server/runs": { "post": { "operationId": "runs-sync-axlymxp-priceline-travel-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/axlymxp~priceline-travel-mcp-server/run-sync": { "post": { "operationId": "run-sync-axlymxp-priceline-travel-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "destination": { "title": "Destination", "type": "string", "description": "City name (auto-resolved) or numeric Priceline geo id. Required only for classic (non-MCP) scraping runs." }, "checkIn": { "title": "Check-in date", "type": "string", "description": "Check-in YYYY-MM-DD (classic run). Defaults to 30 days from today." }, "checkOut": { "title": "Check-out date", "type": "string", "description": "Check-out YYYY-MM-DD (classic run). Defaults to 32 days from today." }, "sort": { "title": "Sort order", "enum": [ "RECOMMENDED", "PRICE", "REVIEW_SCORE" ], "type": "string", "description": "How to sort classic-run results.", "default": "RECOMMENDED" }, "limit": { "title": "Maximum hotels", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Maximum number of hotels to retrieve in a classic run.", "default": 50 } } }, "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 } } } } } } } } } } ```