# Instagram Search Posts Scraper (`data_direct/instagram-posts-scraper`) Actor Search Instagram posts by keyword with engagement metrics - **URL**: https://apify.com/data\_direct/instagram-posts-scraper.md - **Developed by:** [Data Direct](https://apify.com/data_direct) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 pages 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 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 ## Instagram Search Posts Scraper Search for Instagram posts by keyword. Returns post captions, engagement metrics (likes, comments, shares, views), author metadata, hashtags, and mentions. Supports fetching multiple pages in a single API call (billed per page). ### Features - Real-time Instagram data — results are fetched live at run time, never cached or stale - No login, cookies, or proxy configuration needed — just provide the input and run - Each result is pushed as a separate dataset item, exportable as JSON, CSV, or Excel - Fast: a typical run finishes in seconds ### Input | Field | Type | Required | Description | |---|---|---|---| | `query` | string | yes | Search keyword (max 500 characters) | | `pages` | integer | no | Number of pages to fetch and merge into one response (billed per page) | ### Pricing This Actor is billed **per page of results** — **$0.006 per page**. - Results come in pages. Use the `pages` input to choose how many pages to fetch (1–10); more pages means more results. - You pay $0.006 for each page you fetch, so `pages: 3` costs **$0.018** and `pages: 1` costs **$0.006**. - You’re only charged when a run succeeds. Failed runs are free. ### Example output ```json { "count": 20, "pages": 1, "posts": [ { "author": "travelwithasavari", "author_name": "Ankita Vijay Pable", "author_verified": false, "comments": 516, "date": "2026-01-15 23:25:40", "domain": "instagram.com", "hashtags": [ "#CanadaRoadTrip", "#RoadTripCanada", "#TravelCouple", "#ExploreCanada", "#coupletravel" ], "is_video": true, "likes": 77469, "media_type": "clips", "mentions": [], "reposts": 933, "shares": 21562, "snippet": "Buckle up, Canada! \ud83d\ude97\u2728 We're hitting the open road with windows down, coffee in hand, and endless highways. Get ready for hidden gems, iconic landscapes, and core memories in 2026. Slow travel, big views, and unforgettable moments. Save for your next adventure \ud83d\udccd. Where to next? \ud83d\udc40\u2b07\ufe0f #CanadaRoadTrip #RoadTripCanada #TravelCouple #ExploreCanada #coupletravel", "source": "Instagram", "title": "@travelwithasavari on Instagram", "url": "https://instagram.com/p/DTi6c7DEfJL", "views": 2069698, "media_id": "3512345678901234567", "thumbnail_url": "https://scontent.cdninstagram.com/v/t51.82787-15/cover.jpg", "video_url": "https://scontent.cdninstagram.com/o1/v/t2/clip.mp4", "video_duration": 24.5, "width": 1080, "height": 1920, "carousel_media_count": 0, "is_paid_partnership": false, "location": null, "tagged_users": [], "coauthors": [], "carousel_media": [], "audio": { "type": "original", "title": "Original audio", "artist": "travelwithasavari", "audio_id": "1234567890123456", "duration_ms": 24500 } }, { "author" ... (truncated) ```` ### About Maintained by **Data Direct** — a small suite of fast, reliable Instagram and web-data scrapers. Each actor returns clean, structured results with no login, cookies, or proxy setup required. Have a question or a custom data need? Open an issue on this actor. # Actor input Schema ## `query` (type: `string`): Search keyword (max 500 characters) ## `pages` (type: `integer`): Number of pages to fetch and merge into one response (billed per page) ## Actor input object example ```json { "query": "technology", "pages": 1 } ``` # 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": "technology" }; // Run the Actor and wait for it to finish const run = await client.actor("data_direct/instagram-posts-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 = { "query": "technology" } # Run the Actor and wait for it to finish run = client.actor("data_direct/instagram-posts-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 '{ "query": "technology" }' | apify call data_direct/instagram-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_direct/instagram-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Search Posts Scraper", "description": "Search Instagram posts by keyword with engagement metrics", "version": "1.0", "x-build-id": "yIu4gjYThYTKNPdkb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_direct~instagram-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_direct-instagram-posts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_direct~instagram-posts-scraper/runs": { "post": { "operationId": "runs-sync-data_direct-instagram-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_direct~instagram-posts-scraper/run-sync": { "post": { "operationId": "run-sync-data_direct-instagram-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "query" ], "properties": { "query": { "title": "Query", "type": "string", "description": "Search keyword (max 500 characters)" }, "pages": { "title": "Pages", "minimum": 1, "maximum": 10, "type": "integer", "description": "Number of pages to fetch and merge into one response (billed per page)", "default": 1 } } }, "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 } } } } } } } } } } ```