# OpenStreetMap POI Scraper — Local Business Data (`hipersoft/osm-poi-scraper`) Actor Extract points of interest / local businesses from OpenStreetMap by category and area: name, address, coordinates, phone, website, opening hours and more. Free community map data, no anti-bot, no key. Great for lead generation. - **URL**: https://apify.com/hipersoft/osm-poi-scraper.md - **Developed by:** [hiper soft](https://apify.com/hipersoft) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.0008 / poi scraped 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 ## OpenStreetMap POI Scraper — local business data by category & area, address, phone, coordinates & hours, no API key Extract points of interest and local businesses from OpenStreetMap by category and area. Give it a place name and a category and get back clean, structured JSON: name, full address, coordinates, phone, website, email, and opening hours. Backed by free community map data with no anti-bot layer — no account, no API key. Great for lead generation, local market research, and building location datasets. ### Features - 🗂️ **20 ready categories** — pick from restaurants, cafes, bars, hotels, supermarkets, pharmacies, banks, gyms, and more via `category`, or use `custom`. - 🏷️ **Custom tag filters** — with `category: custom`, target any OSM tags via `customFilters` like `shop=bakery` or `tourism=museum`. - 📍 **Full location data** — each POI carries `latitude`/`longitude`, a structured address, plus ready `osmUrl` and `googleMapsUrl` links. - ☎️ **Contact details** — `phone`, `website`, and `email` pulled from OSM contact tags where present. - 🕒 **Rich attributes** — `openingHours`, `cuisine`, `brand`, `operator`, and `wheelchair` accessibility, plus the raw `tags` object. - 🌍 **Any area, auto-geocoded** — pass place names like `Austin, Texas` or `Berlin`; each is geocoded to a bounding box automatically. - 🔢 **Volume control** — cap output with `maxItemsPerArea` (up to 10000); results are deduplicated per area. ### What you get Each row is one point of interest: ```json { "name": "Franklin Barbecue", "category": "restaurant", "area": "Austin, Texas", "street": "East 11th Street", "houseNumber": "900", "city": "Austin", "postcode": "78702", "country": "United States", "phone": "+1-512-653-1187", "website": "https://franklinbbq.com", "email": null, "openingHours": "Tu-Su 11:00-15:00", "cuisine": "barbecue", "brand": null, "operator": null, "wheelchair": "yes", "latitude": 30.2701, "longitude": -97.7314, "osmType": "node", "osmId": 123456789, "osmUrl": "https://www.openstreetmap.org/node/123456789", "googleMapsUrl": "https://www.google.com/maps/search/?api=1&query=30.2701,-97.7314", "tags": { "amenity": "restaurant", "name": "Franklin Barbecue" } } ```` ### Input ```json { "areas": ["Austin, Texas", "Berlin, Germany"], "category": "restaurant", "maxItemsPerArea": 500 } ``` | Field | Description | |-------|-------------| | `areas` | Place names to search within; each is geocoded to a bounding box (required). | | `category` | Type of place, e.g. `restaurant`, `cafe`, `hotel`, `pharmacy`, or `custom`. Default `restaurant`. | | `customFilters` | For `category: custom`, OSM `key=value` tags like `shop=bakery`; any match is included. | | `maxItemsPerArea` | Maximum POIs to collect per area, 1–10000. Default `500`. | ### Use cases - Build local-business lead lists with names, phones, and websites. - Research market density and competitors in a target area. - Enrich CRM or mapping data with coordinates and opening hours. - Assemble category-specific place datasets across multiple cities. ### Pricing Pay-per-event: you're billed a small amount per run and per item scraped — you only pay for what you get. See the **Pricing** tab for current rates. ### Notes This Actor uses OpenStreetMap's public Nominatim and Overpass APIs and returns only openly available community-contributed map data. It is an independent tool and is not affiliated with or endorsed by the OpenStreetMap Foundation; OpenStreetMap is a trademark of its respective owner. Please respect OSM data usage and attribution guidelines. # Actor input Schema ## `areas` (type: `array`): Place names to search within, e.g. "Austin, Texas" or "Berlin". Each is geocoded to a bounding box. ## `category` (type: `string`): Type of place to find. ## `customFilters` (type: `array`): For category "custom": OSM key=value tags, e.g. "shop=bakery", "tourism=museum". Any match is included. ## `maxItemsPerArea` (type: `integer`): Maximum POIs to collect per area. ## Actor input object example ```json { "areas": [ "Berlin, Germany", "Manhattan, New York" ], "category": "restaurant", "customFilters": [ "shop=bakery", "amenity=cinema" ], "maxItemsPerArea": 500 } ``` # 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 = { "areas": [ "Austin, Texas" ] }; // Run the Actor and wait for it to finish const run = await client.actor("hipersoft/osm-poi-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 = { "areas": ["Austin, Texas"] } # Run the Actor and wait for it to finish run = client.actor("hipersoft/osm-poi-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 '{ "areas": [ "Austin, Texas" ] }' | apify call hipersoft/osm-poi-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hipersoft/osm-poi-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OpenStreetMap POI Scraper — Local Business Data", "description": "Extract points of interest / local businesses from OpenStreetMap by category and area: name, address, coordinates, phone, website, opening hours and more. Free community map data, no anti-bot, no key. Great for lead generation.", "version": "1.0", "x-build-id": "Tw6qeApjqGWOJTfd5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hipersoft~osm-poi-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hipersoft-osm-poi-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hipersoft~osm-poi-scraper/runs": { "post": { "operationId": "runs-sync-hipersoft-osm-poi-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hipersoft~osm-poi-scraper/run-sync": { "post": { "operationId": "run-sync-hipersoft-osm-poi-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "areas": { "title": "Areas", "type": "array", "description": "Place names to search within, e.g. \"Austin, Texas\" or \"Berlin\". Each is geocoded to a bounding box.", "items": { "type": "string" } }, "category": { "title": "Category", "enum": [ "restaurant", "cafe", "bar", "fast_food", "hotel", "supermarket", "pharmacy", "bank", "fuel", "hospital", "doctors", "dentist", "gym", "bakery", "clothes_shop", "hairdresser", "car_repair", "lawyer", "school", "custom" ], "type": "string", "description": "Type of place to find.", "default": "restaurant" }, "customFilters": { "title": "Custom tag filters", "type": "array", "description": "For category \"custom\": OSM key=value tags, e.g. \"shop=bakery\", \"tourism=museum\". Any match is included.", "items": { "type": "string" } }, "maxItemsPerArea": { "title": "Max items per area", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum POIs to collect per area.", "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 } } } } } } } } } } ```