# Instagram Tagged Posts & Mentions Scraper ยท No Login (`data-slayer/instagram-tagged-posts`) Actor Extract every Instagram post where any account is tagged โ€” no login. 126 fields per post: captions, likes, comments, tagged users, media URLs, and timestamps. Brand mention monitoring, UGC discovery, influencer campaign verification. No cookies. JSON/CSV/Excel. - **URL**: https://apify.com/data-slayer/instagram-tagged-posts.md - **Developed by:** [Data Slayer](https://apify.com/data-slayer) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Tagged Posts & Mentions Scraper ยท No Login Enter any Instagram username and get every post where that account is tagged by other people. 126 data fields per post including engagement metrics, captions, media URLs, and poster profiles. Brand monitoring, UGC discovery, influencer campaign verification. No login required. ### What You Get 126 fields per tagged post. Key ones: #### Engagement metrics | Field | Description | |---|---| | `like_count` | Total likes on the post | | `comment_count` | Total comments | | `play_count` | Views (for video posts) | | `ig_play_count` | Instagram-native view count | #### Content data | Field | Description | |---|---| | `caption.text` | Full caption | | `caption.hashtags` | Pre-parsed hashtag array | | `caption.mentions` | Pre-parsed @mentions array | | `video_url` | Direct video URL | | `thumbnail_url` | Thumbnail image | | `taken_at_date` | Post date | | `media_type` | 1=image, 2=video, 8=carousel | | `tagged_users` | All accounts tagged in the post | | `coauthor_producers` | Collaboration partners | | `is_paid_partnership` | Sponsored content flag | #### Poster profile (who tagged you) | Field | Description | |---|---| | `user.username` | Who posted it | | `user.full_name` | Display name | | `user.is_verified` | Blue check status | | `user.profile_pic_url` | Profile picture | #### Location (when tagged) | Field | Description | |---|---| | `location.name` | Tagged location name | | `location.lat` / `location.lng` | GPS coordinates | ### How It Works **Step 1.** Enter the username you want to monitor (e.g., `nike`, `glossier`, or your own brand handle). **Step 2.** Click "Start." The actor extracts all posts where that account is tagged. **Step 3.** Download as JSON, CSV, or Excel. ### ๐Ÿ“บ Video Tutorial *Coming soon* --- ### Use Cases **Brand mention monitoring.** Enter your brand's username โ†’ see every post where customers, partners, and influencers have tagged you. Measure your earned media volume, track sentiment in captions, and identify who's talking about your brand without being asked to. **UGC discovery and rights management.** Find authentic user-generated content featuring your products. Sort by `like_count` to find the best-performing UGC. Extract the poster's username and run it through [Instagram Contact & Email Finder](https://apify.com/data-slayer/instagram-user-info-scraper-cookieless) to reach out for reposting permission or paid partnerships. **Influencer campaign verification.** After a campaign, verify deliverables: did the influencer tag your brand in the agreed posts? How much engagement did those posts get? Export the data for ROI reporting without manual checking. **Competitor brand monitoring.** Enter a competitor's username โ†’ see who creates content about them, what performs well, and identify their organic advocates. Those advocates are prospects for your brand. **Partnership discovery.** Find accounts that regularly tag your brand without being paid. These are your most authentic advocates โ€” ideal candidates for ambassador programs, affiliates, or paid partnerships. They already know and love your brand. --- ### Sample Output ```json { "like_count": 847, "comment_count": 23, "play_count": 12400, "taken_at_date": "2026-05-01T18:32:25+00:00", "caption": { "text": "Wearing my favourite @nike kicks today ๐Ÿƒ #running", "hashtags": ["#running"], "mentions": ["@nike"] }, "tagged_users": [ { "user": { "username": "nike", "full_name": "nike", "is_verified": true } } ], "video_url": null, "thumbnail_url": "https://scontent.cdninstagram.com/...", "media_type": 1, "user": { "username": "cityexplorer_nyc", "full_name": "Sarah Mitchell", "is_verified": false } } ```` *** ### Key Features **126 fields per post.** Full engagement metrics, pre-parsed captions, tagged user objects, collaborator data, media URLs, and location data. **Pre-parsed captions.** Hashtags and mentions as separate arrays โ€” no regex needed. **No login, no cookies.** No Instagram account required. No ban risk. **Export-ready.** JSON, CSV, Excel. Works with Make, Zapier, n8n, Clay, and any CRM. *** ### Note on Share Count Instagram's API does not expose share counts for tagged posts. All other engagement metrics (likes, comments, views) are fully available. *** ### FAQ **What's the difference between tagged posts and @mentions in captions?** This actor captures posts where your account is tagged in the image itself (photo tags) โ€” which are higher-signal than caption mentions. Caption @mentions are also captured in `caption.mentions` for completeness. **How many tagged posts can I get?** Depends on how much content is tagged with that username. Popular brands may have thousands. The actor paginates automatically. **Can I get contact info for the people who tagged me?** Yes. Take the `user.username` values from this actor's output and run them through [Instagram Contact & Email Finder](https://apify.com/data-slayer/instagram-user-info-scraper-cookieless) to get emails and phone numbers. *** ### ๐Ÿงฉ Other Instagram Actors by Data Slayer | Actor | What it does | Link | |---|---|---| | Instagram Contact & Email Finder | Emails & phones from profiles | [Try it โ†’](https://apify.com/data-slayer/instagram-user-info-scraper-cookieless) | | Instagram Reposts Tracker | Who reposted content from a profile | [Try it โ†’](https://apify.com/data-slayer/instagram-reposts) | | Instagram Profile Posts | All posts from any profile | [Try it โ†’](https://apify.com/data-slayer/instagram-posts) | | Instagram Comments Extractor | Comments with engagement intelligence | [Try it โ†’](https://apify.com/data-slayer/instagram-comments-scraper-no-login-required) | | Instagram Reels Search | Discover trending Reels by keyword | [Try it โ†’](https://apify.com/data-slayer/instagram-search-reels) | | Instagram Profile Reels | All Reels from any profile | [Try it โ†’](https://apify.com/data-slayer/instagram-profile-reels) | *** ### ๐Ÿ’ฌ Feedback & Support We actively maintain this actor and ship improvements weekly. Open an issue on the **Issues tab** or leave a rating. We respond within 24 hours. # Actor input Schema ## `username` (type: `string`): Instagram username to monitor for tags ## `maxResults` (type: `integer`): Maximum number of tagged posts to return ## Actor input object example ```json { "username": "nike", "maxResults": 50 } ``` # 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 = { "username": "nike" }; // Run the Actor and wait for it to finish const run = await client.actor("data-slayer/instagram-tagged-posts").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "username": "nike" } # Run the Actor and wait for it to finish run = client.actor("data-slayer/instagram-tagged-posts").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "username": "nike" }' | apify call data-slayer/instagram-tagged-posts --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data-slayer/instagram-tagged-posts", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Tagged Posts & Mentions Scraper ยท No Login", "description": "Extract every Instagram post where any account is tagged โ€” no login. 126 fields per post: captions, likes, comments, tagged users, media URLs, and timestamps. Brand mention monitoring, UGC discovery, influencer campaign verification. No cookies. JSON/CSV/Excel.", "version": "1.0", "x-build-id": "I2xfwi1Qp39aJzmYf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data-slayer~instagram-tagged-posts/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data-slayer-instagram-tagged-posts", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data-slayer~instagram-tagged-posts/runs": { "post": { "operationId": "runs-sync-data-slayer-instagram-tagged-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data-slayer~instagram-tagged-posts/run-sync": { "post": { "operationId": "run-sync-data-slayer-instagram-tagged-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "username" ], "properties": { "username": { "title": "Instagram Username", "type": "string", "description": "Instagram username to monitor for tags" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of tagged posts to return", "default": 50 } } }, "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 } } } } } } } } } } ```