# Instagram Comments Scraper (`seemuapps/instagram-comments-scraper`) Actor Scrape all comments from any public Instagram post or Reel comment text, author profile, like count, and timestamp. Just paste the post URL. - **URL**: https://apify.com/seemuapps/instagram-comments-scraper.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** Social media, Lead generation, Developer tools - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 single comments 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 ## Instagram Comments Scraper Extract every comment from any public Instagram post or Reel — comment text, author profile, like counts, and timestamps. No login or cookies required. ### What you get For every comment on a post, the scraper returns a structured record with: **Comment data** - Comment ID and full text - Created timestamp (ISO 8601 and Unix) - Like count and reply count **Author profile** - Author ID, username, full name - Profile picture URL - Verified and private flags **Post reference** - Post ID, shortcode, and post URL on every record **Pagination** - `NEXT_PAGE_ID` cursor so you can resume from where a previous run left off ### Use cases - **Sentiment analysis** — pull every comment on a post to measure audience reaction - **Customer feedback** — capture questions and complaints under product or campaign posts - **Lead generation** — collect engaged commenters and their profiles for outreach - **Community research** — find your most active fans and biggest critics - **Influencer vetting** — check comment quality and authenticity before a partnership - **Giveaway & contest management** — export all entrants who commented on a post ### How to use 1. Paste the Instagram post or Reel — the full URL (e.g. `https://www.instagram.com/p/DZIoOtwvkpG/`) or just the shortcode (`DZIoOtwvkpG`) 2. Set **Max Comments** — default 100 per run, or 0 for unlimited (will stop ~60s before the actor timeout) 3. Run the actor — results appear in the **Dataset** tab 4. To fetch the next page, copy `NEXT_PAGE_ID` from the **Key-value store** tab and paste it into **Page ID** on the next run ### Output format Each dataset record: ```json { "commentId": "18082281662325661", "text": "So Beautiful 😍", "createdAt": "2026-06-03T19:10:42.000Z", "createdAtTimestamp": 1780513842, "likeCount": 12, "replyCount": 0, "postId": "3911553209440553542", "postShortcode": "DZIoOtwvkpG", "postUrl": "https://www.instagram.com/p/DZIoOtwvkpG/", "authorId": "3268463675", "authorUsername": "easyenglishwithkekemu", "authorFullName": "Easy English With Kekemu", "authorProfilePicUrl": "https://scontent.cdninstagram.com/...", "authorIsVerified": false, "authorIsPrivate": false } ```` ### Pagination Each run returns up to **Max Comments** records. For posts with thousands of comments, use the pagination cursor to collect more across multiple runs: 1. Run the actor — when it finishes, `NEXT_PAGE_ID` is saved in the **Key-value store** tab 2. Copy the `NEXT_PAGE_ID` value 3. Start a new run with the same post and paste it into the **Page ID** field 4. Repeat until `NEXT_PAGE_ID` is `null` (all comments fetched) If a single run reaches the actor timeout, the cursor still gets written before the run ends so you can resume on the next run. # Actor input Schema ## `post` (type: `string`): Instagram post or Reel — paste the full URL (e.g. https://www.instagram.com/p/DZIoOtwvkpG/) or just the shortcode (DZIoOtwvkpG). ## `maxItems` (type: `integer`): Maximum number of comments to scrape. Set 0 for unlimited (caps at platform timeout). ## `pageId` (type: `string`): Optional. Paste NEXT\_PAGE\_ID from the previous run's Key-value store to fetch the next page of comments. ## Actor input object example ```json { "post": "https://www.instagram.com/p/DZIoOtwvkpG/", "maxItems": 100 } ``` # Actor output Schema ## `results` (type: `string`): Each record contains commentId, text, createdAt, createdAtTimestamp, likeCount, replyCount, postId, postShortcode, postUrl, and author fields (authorId, authorUsername, authorFullName, authorProfilePicUrl, authorIsVerified, authorIsPrivate). ## `nextPageId` (type: `string`): NEXT\_PAGE\_ID record in the default key-value store. Paste into Page ID on the next run to resume; null when all comments are fetched. # 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 = { "post": "https://www.instagram.com/p/DZIoOtwvkpG/" }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/instagram-comments-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 = { "post": "https://www.instagram.com/p/DZIoOtwvkpG/" } # Run the Actor and wait for it to finish run = client.actor("seemuapps/instagram-comments-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 '{ "post": "https://www.instagram.com/p/DZIoOtwvkpG/" }' | apify call seemuapps/instagram-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/instagram-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Comments Scraper", "description": "Scrape all comments from any public Instagram post or Reel comment text, author profile, like count, and timestamp. Just paste the post URL.", "version": "1.0", "x-build-id": "K1x5wIMYXmERr8N1J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~instagram-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-instagram-comments-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~instagram-comments-scraper/runs": { "post": { "operationId": "runs-sync-seemuapps-instagram-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~instagram-comments-scraper/run-sync": { "post": { "operationId": "run-sync-seemuapps-instagram-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "post" ], "properties": { "post": { "title": "Post URL or shortcode", "type": "string", "description": "Instagram post or Reel — paste the full URL (e.g. https://www.instagram.com/p/DZIoOtwvkpG/) or just the shortcode (DZIoOtwvkpG)." }, "maxItems": { "title": "Max Comments", "minimum": 0, "type": "integer", "description": "Maximum number of comments to scrape. Set 0 for unlimited (caps at platform timeout).", "default": 100 }, "pageId": { "title": "Page ID (pagination)", "type": "string", "description": "Optional. Paste NEXT_PAGE_ID from the previous run's Key-value store to fetch the next page of comments." } } }, "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 } } } } } } } } } } ```