# US Travel Advisories Scraper — State Department Country Risk (`compute-edge/us-travel-advisories-scraper`) Actor Extract all US State Department travel advisories — country risk levels 1-4, extracted risk factors (crime, terrorism, kidnapping), and clean plain-text summaries ready for LLM/RAG pipelines. Filter by minimum level or country. - **URL**: https://apify.com/compute-edge/us-travel-advisories-scraper.md - **Developed by:** [Compute Edge](https://apify.com/compute-edge) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results 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 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 ## US State Department Travel Advisories Scraper Extract **every active US State Department travel advisory** — country risk levels, extracted risk factors, and clean plain-text advisory summaries — as structured JSON ready for dashboards, alerts, and AI pipelines. The US State Department maintains travel advisories for roughly 200 countries and territories, rated on a four-level scale from **Level 1 (Exercise Normal Precautions)** to **Level 4 (Do Not Travel)**. These advisories drive corporate travel policy, insurance underwriting, and duty-of-care obligations worldwide. This Actor pulls the full advisory list from the State Department's public API in a single run, parses the risk level out of each title, extracts the highlighted **risk factors** (crime, terrorism, kidnapping, civil unrest, health infrastructure…), and converts the HTML advisory body into **clean, LLM/RAG-ready plain text**. ### Who uses this data? - **Travel risk management and duty-of-care platforms** keeping country risk ratings current - **Corporate security teams** triggering policy reviews when a destination's level changes - **Travel insurers and underwriters** pricing country risk - **Airlines, OTAs, and tour operators** surfacing advisory levels at booking time - **Expat services and relocation firms** briefing clients on destination risk - **AI travel assistants** grounding answers in official government advisories ### Data fields | Field | Description | |-------|-------------| | `country` | Country or territory name | | `advisoryLevel` | Numeric risk level 1–4 | | `advisoryLevelText` | Level description (e.g. "Reconsider Travel") | | `riskFactors` | Extracted risk keywords (crime, terrorism, kidnapping…) | | `summaryText` | Full advisory text, HTML stripped — plain text, RAG-ready | | `countryCodes` | Country code(s) from the State Department feed | | `link` | Direct URL to the official advisory page | | `title` | Original advisory title | | `fetchedAt` | Timestamp of the run | ### How to scrape US travel advisories 1. Run with **empty input** to get all ~200 advisories, sorted highest-risk first. 2. Or set **Minimum Advisory Level** (e.g. `3`) to get only Reconsider Travel / Do Not Travel countries. 3. Or set a **Country Filter** (e.g. `mexico`) for a single destination. 4. Download results from the **Dataset** tab as JSON, CSV, or Excel. ### Input example ```json { "minLevel": 3, "countryFilter": "", "maxResults": 500 } ```` ### Output example ```json { "country": "Venezuela", "advisoryLevel": 3, "advisoryLevelText": "Reconsider Travel", "riskFactors": ["crime", "kidnapping", "terrorism", "poor health infrastructure"], "summaryText": "Reconsider travel to Venezuela due to risk of crime, kidnapping, terrorism, and poor health infrastructure...", "countryCodes": ["VE"], "link": "https://travel.state.gov/content/tsg_aem/us/en/home/international-travel/travel-advisories/destination.ven.html" } ``` ### Pricing You pay a small fee per result plus standard Apify compute. A full run (~200 advisories) completes in seconds at the smallest memory setting — schedule it daily for change monitoring. ### FAQ **How often do advisories change?** The State Department reviews Level 1–2 advisories at least every 12 months and Level 3–4 advisories at least every 6 months, plus immediate updates after significant events. **How do I detect level changes?** Schedule this Actor daily and diff `advisoryLevel` per country between runs. **Are regional advisories within a country included?** The dataset is one record per country-level advisory; regional detail is preserved inside `summaryText`. ### Legal disclaimer This Actor extracts publicly available data published by the US Department of State, a US government agency. The data is in the public domain. This Actor is not affiliated with or endorsed by the Department of State. Advisory data is informational; always check the official advisory page before making travel decisions. # Actor input Schema ## `minLevel` (type: `integer`): Only include advisories at or above this level. 1 = Exercise Normal Precautions, 2 = Exercise Increased Caution, 3 = Reconsider Travel, 4 = Do Not Travel. ## `countryFilter` (type: `string`): Filter by country name (case-insensitive partial match). Example: 'mexico'. ## `maxResults` (type: `integer`): Maximum number of advisories to return. ## Actor input object example ```json { "minLevel": 1, "countryFilter": "", "maxResults": 500 } ``` # Actor output Schema ## `dataset` (type: `string`): No description # 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("compute-edge/us-travel-advisories-scraper").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("compute-edge/us-travel-advisories-scraper").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 compute-edge/us-travel-advisories-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=compute-edge/us-travel-advisories-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "US Travel Advisories Scraper — State Department Country Risk", "description": "Extract all US State Department travel advisories — country risk levels 1-4, extracted risk factors (crime, terrorism, kidnapping), and clean plain-text summaries ready for LLM/RAG pipelines. Filter by minimum level or country.", "version": "0.1", "x-build-id": "n07Yh2t6MOx0hV4oU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/compute-edge~us-travel-advisories-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-compute-edge-us-travel-advisories-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/compute-edge~us-travel-advisories-scraper/runs": { "post": { "operationId": "runs-sync-compute-edge-us-travel-advisories-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/compute-edge~us-travel-advisories-scraper/run-sync": { "post": { "operationId": "run-sync-compute-edge-us-travel-advisories-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "minLevel": { "title": "Minimum Advisory Level", "minimum": 1, "maximum": 4, "type": "integer", "description": "Only include advisories at or above this level. 1 = Exercise Normal Precautions, 2 = Exercise Increased Caution, 3 = Reconsider Travel, 4 = Do Not Travel.", "default": 1 }, "countryFilter": { "title": "Country Filter", "type": "string", "description": "Filter by country name (case-insensitive partial match). Example: 'mexico'.", "default": "" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of advisories to return.", "default": 500 } } }, "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 } } } } } } } } } } ```