# Tripadvisor Attractions MCP Server (`axlymxp/tripadvisor-attractions-mcp`) Actor Tripadvisor Attractions MCP Server for AI agents. Give Claude, Cursor or ChatGPT live tools to search destinations, list a city's top things to do, and fetch attraction details — ratings, reviews, categories, GPS. Also runs as a classic scraper. Pay per tool call. - **URL**: https://apify.com/axlymxp/tripadvisor-attractions-mcp.md - **Developed by:** [axly](https://apify.com/axlymxp) (community) - **Categories:** Travel, Developer tools, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event + usage 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 ## Tripadvisor Attractions MCP Server Give your AI assistant **live access to Tripadvisor attractions**. This actor runs as a **Model Context Protocol (MCP) server** so agents like Claude, Cursor, ChatGPT and n8n can search destinations, list a city's top things to do, and fetch attraction details on demand — and it also works as a classic one-shot scraper. Built on Tripadvisor's **mobile API** (static key, no DataDome), so tool calls stay reliable. ### Who uses this - **AI agent / app builders** — add real Tripadvisor data to a chatbot, trip planner or research agent without maintaining a scraper. - **Analysts & researchers** — query attractions ad hoc from an assistant. - **Travel product teams** — prototype destination features with live data. ### MCP tools | Tool | What it does | | ------------------------- | --------------------------------------------------------------------------- | | `search_tripadvisor_geos` | Resolve free text to Tripadvisor destinations (geo id, name, type, route). | | `list_attractions` | Ranked things to do for a city/geo — rating, reviews, category, GPS, photo. | | `get_attraction` | Detail for one attraction — rating, reviews, canonical tripadvisor.com URL. | ### Connect it Start the actor in **Standby** mode and point your MCP client at: ```` https:///mcp ```` Example (Claude Desktop / Cursor config): ```json { "mcpServers": { "tripadvisor": { "url": "https:///mcp" } } } ```` Then ask your agent things like *"List the top 10 things to do in Rome with their ratings and coordinates"* or *"Find the Tripadvisor geo id for Kyoto"*. ### Classic scraper mode Prefer a one-shot dataset run? Provide `query` (a city name or geo id) and the actor pushes that city's attractions to the dataset — handy for scheduled jobs. #### Output fields (list\_attractions / dataset) | Field | Type | Description | | -------------- | ------- | --------------------------- | | `location_id` | integer | Tripadvisor attraction id | | `name` | string | Attraction name | | `rank` | integer | Ranked position in the city | | `rating` | number | Average bubble rating (0–5) | | `review_count` | integer | Traveler reviews | | `category` | string | Attraction category | | `latitude` | number | GPS latitude | | `longitude` | number | GPS longitude | | `image_url` | string | Primary photo URL | | `geo_id` | integer | City/region geo id | | `geo_name` | string | City/region name | ### Example (classic run) input ```json { "query": "Paris", "limit": 20, "includeCoordinates": true } ``` ### FAQ **How do agents use it?** Start it in Standby mode and connect any MCP client to `/mcp` (Streamable HTTP). The three tools appear automatically. **Where does the data come from?** Tripadvisor's mobile app API — the same data the app shows for a destination's "Things to Do". **Is it reliable?** The mobile API is not behind the website's DataDome challenge, so tool calls are stable. **Is scraping this legal?** You are responsible for complying with Tripadvisor's terms and applicable laws; use only public data and reasonable rates. # Actor input Schema ## `query` (type: `string`): Classic-run mode only: a city/place name (e.g. "Rome") or numeric Tripadvisor geo id. Leave empty to run as an MCP server in Standby mode. ## `limit` (type: `integer`): Classic-run mode: max attractions to return. ## `includeTourProducts` (type: `boolean`): Also include bookable tours/experiences. ## `includeCoordinates` (type: `boolean`): Attach latitude/longitude to each attraction. ## Actor input object example ```json { "query": "Paris", "limit": 30, "includeTourProducts": false, "includeCoordinates": 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 = { "query": "Paris" }; // Run the Actor and wait for it to finish const run = await client.actor("axlymxp/tripadvisor-attractions-mcp").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 = { "query": "Paris" } # Run the Actor and wait for it to finish run = client.actor("axlymxp/tripadvisor-attractions-mcp").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 '{ "query": "Paris" }' | apify call axlymxp/tripadvisor-attractions-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=axlymxp/tripadvisor-attractions-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tripadvisor Attractions MCP Server", "description": "Tripadvisor Attractions MCP Server for AI agents. Give Claude, Cursor or ChatGPT live tools to search destinations, list a city's top things to do, and fetch attraction details — ratings, reviews, categories, GPS. Also runs as a classic scraper. Pay per tool call.", "version": "1.0", "x-build-id": "fGCeCCnYuqohCY4V6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/axlymxp~tripadvisor-attractions-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-axlymxp-tripadvisor-attractions-mcp", "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~tripadvisor-attractions-mcp/runs": { "post": { "operationId": "runs-sync-axlymxp-tripadvisor-attractions-mcp", "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~tripadvisor-attractions-mcp/run-sync": { "post": { "operationId": "run-sync-axlymxp-tripadvisor-attractions-mcp", "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": { "query": { "title": "City / place or geo ID", "type": "string", "description": "Classic-run mode only: a city/place name (e.g. \"Rome\") or numeric Tripadvisor geo id. Leave empty to run as an MCP server in Standby mode." }, "limit": { "title": "Max attractions", "minimum": 1, "maximum": 200, "type": "integer", "description": "Classic-run mode: max attractions to return.", "default": 30 }, "includeTourProducts": { "title": "Include tours & activities", "type": "boolean", "description": "Also include bookable tours/experiences.", "default": false }, "includeCoordinates": { "title": "Include GPS coordinates", "type": "boolean", "description": "Attach latitude/longitude to each attraction.", "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 } } } } } } } } } } ```