# Restaurant Intelligence (OpenStreetMap) (`osmateus/restaurant-intelligence-api`) Actor Extract restaurant pricing, ratings, availability and trends from OpenTable and Resy. Restaurant market research and competitive intelligence API. - **URL**: https://apify.com/osmateus/restaurant-intelligence-api.md - **Developed by:** [Mateo Tejeda](https://apify.com/osmateus) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## OSM Restaurant Directory API OSM Restaurant Directory API helps teams collect OpenStreetMap restaurants, restaurant directory, local business data as clean JSON on Apify. It uses OpenStreetMap Overpass API, so the listing matches the real data source used by the Actor. Find restaurants in any city from OpenStreetMap Overpass with names, cuisine, coordinates, phone, website, and opening hours. The Actor does not use OpenTable, Resy, or reservation platforms. It queries OpenStreetMap data via the public Overpass API and returns restaurants tagged with `amenity=restaurant`. Results can be filtered by city and optional cuisine keyword, then exported from Apify as JSON, CSV, Excel, or through the dataset API. OpenStreetMap is community-maintained geospatial data, so coverage varies by city, but it is an excellent source for public restaurant names, cuisines, coordinates, addresses, websites, phone numbers, opening hours, OSM IDs, and OpenStreetMap URLs. This makes the Actor useful for building local directories, finding restaurant clusters, enriching maps, preparing sales lists, and analyzing food-service coverage in specific markets. ### What You Get - Restaurant records from OpenStreetMap using Overpass API - Name, city, cuisine, amenity type, latitude, longitude, address, phone, website, opening hours, OSM ID, OSM type, and URL when available - Optional cuisine filtering such as Italian, sushi, vegan, pizza, or cafe-style terms - Clean Apify dataset output for no-code automations and API pipelines - No login, no reservation-site scraping, no browser automation, and no private user data ### Input Example ```json { "city": "Madrid", "cuisine": "Italian", "maxResults": 20 } ```` ### Output Example ```json { "rank": 1, "name": "La Tagliatella", "city": "Madrid", "cuisine": "italian", "amenity": "restaurant", "lat": 40.4168, "lon": -3.7038, "address": "Calle Mayor 12", "phone": "+34 900 000 000", "website": "https://example.com", "opening_hours": "Mo-Su 12:00-23:30", "osm_id": 987654321, "osm_type": "node", "url": "https://www.openstreetmap.org/node/987654321", "fetched_at": "2026-07-06T10:30:00.000Z" } ``` Use it for restaurant lead generation, local market mapping, competitive discovery, and OpenStreetMap restaurant data extraction. # Actor input Schema ## `city` (type: `string`): City to search in OpenStreetMap Overpass, such as Madrid, London, Berlin, or New York. ## `cuisine` (type: `string`): Optional OpenStreetMap cuisine filter, such as Italian, sushi, vegan, or pizza. ## `maxResults` (type: `integer`): Cap on named restaurant results returned (5-100). ## Actor input object example ```json { "city": "Madrid", "cuisine": "", "maxResults": 20 } ``` # Actor output Schema ## `results` (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("osmateus/restaurant-intelligence-api").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("osmateus/restaurant-intelligence-api").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 osmateus/restaurant-intelligence-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=osmateus/restaurant-intelligence-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Restaurant Intelligence (OpenStreetMap)", "description": "Extract restaurant pricing, ratings, availability and trends from OpenTable and Resy. Restaurant market research and competitive intelligence API.", "version": "0.1", "x-build-id": "ZkRuIfUP2Xk3dISCt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/osmateus~restaurant-intelligence-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-osmateus-restaurant-intelligence-api", "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/osmateus~restaurant-intelligence-api/runs": { "post": { "operationId": "runs-sync-osmateus-restaurant-intelligence-api", "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/osmateus~restaurant-intelligence-api/run-sync": { "post": { "operationId": "run-sync-osmateus-restaurant-intelligence-api", "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": { "city": { "title": "City name", "type": "string", "description": "City to search in OpenStreetMap Overpass, such as Madrid, London, Berlin, or New York.", "default": "Madrid" }, "cuisine": { "title": "Cuisine filter (optional)", "type": "string", "description": "Optional OpenStreetMap cuisine filter, such as Italian, sushi, vegan, or pizza.", "default": "" }, "maxResults": { "title": "Max results", "minimum": 5, "maximum": 100, "type": "integer", "description": "Cap on named restaurant results returned (5-100).", "default": 20 } } }, "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 } } } } } } } } } } ```