# Instagram Active Story Profiles by Cookies (`shareze001/instagram-active-story-profiles-by-cookies`) Actor Uses valid Instagram session cookies to read your active stories tray and list followed accounts that have an active Story right now (not your full following list). Returns username, id, profile picture, and story timing fields. Cookies: browser DevTools or the shareze001/instagram-cookies Actor. - **URL**: https://apify.com/shareze001/instagram-active-story-profiles-by-cookies.md - **Developed by:** [shareze](https://apify.com/shareze001) (community) - **Categories:** Social media, Videos, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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. 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 ### What this Actor does **Instagram Active Story Profiles by Cookies** uses your **logged-in Instagram session** (passed as browser cookies) to read the same **stories tray** data Instagram shows when you open [instagram.com](https://www.instagram.com/) while logged in. From that feed it returns **accounts you follow that currently have active Stories** (profiles with a story ring), along with basic profile fields and story timing metadata. It does **not** log in for you: you must supply **valid cookies** from an active session (typically including `sessionid`). You can copy cookies from your browser after logging in, **or** get them from the [`shareze001/instagram-cookies`](https://apify.com/shareze001/instagram-cookies) Actor on Apify. ### Input Configure the Actor on the **Input** tab in Apify Console or via JSON. The only required field is: | Field | Type | Description | | --- | --- | --- | | **cookies** | string | Full `Cookie` header string (e.g. `sessionid=...; csrftoken=...; ...`). **Sources:** (1) Your browser—log into Instagram, then copy the `Cookie` header from DevTools; (2) **[`shareze001/instagram-cookies`](https://apify.com/shareze001/instagram-cookies)**—run that Actor on Apify and use the cookie string it outputs as the value here. | **Validation:** The input must contain a real `sessionid` and must not be the placeholder `sessionid=xxxxxx`. Otherwise the run finishes with an error message in the dataset (see Output). Example JSON: ```json { "cookies": "sessionid=YOUR_SESSION_ID; csrftoken=YOUR_CSRF; ..." } ```` ### Output Results are written to the Actor’s **default dataset**. You can download them as JSON, CSV, Excel, etc., from the run’s **Dataset** tab or via the Apify API. #### Successful rows (one object per profile with Stories) Each item includes: | Field | Description | | --- | --- | | **user\_id** | Instagram user id | | **username** | Handle | | **profile\_pic\_url** | Profile picture URL | | **expiring\_at** | Story expiry timestamp (when provided by the feed) | | **latest\_reel\_media** | Latest reel/story media metadata (when provided) | Example (illustrative): ```json [ { "user_id": "123456789", "username": "example_user", "profile_pic_url": "https://instagram.com/...", "expiring_at": 1710000000, "latest_reel_media": 1709990000 } ] ``` #### Messages instead of profile rows The dataset may contain a **single object** with a `message` field when no list of profiles is returned, for example: - Invalid or missing cookies: `Provide a logged-in cookie.` - No matching tray data or no accounts with Stories: `No story profiles found.` If the session is **expired or rejected**, the Actor may log an error and return no usable tray payload—refresh your cookies and run again. ### Related: fetch each profile’s Stories This Actor only lists **who** has an active Story (and basic metadata). To **fetch that profile’s Stories** (media/items), use **[`shareze001/scrape-instagram-story-by-cookies`](https://apify.com/shareze001/scrape-instagram-story-by-cookies)** on Apify. Its input includes **`username`**—use the same **`username`** value from a row in this Actor’s dataset. Typical flow: run this Actor → for each **`username`** you need, run **scrape-instagram-story-by-cookies** with that handle. *** **Disclaimer:** Use this Actor only in line with [Instagram’s Terms of Use](https://help.instagram.com/581066165581870) and applicable laws. You are responsible for the account and cookies you use. # Actor input Schema ## `cookies` (type: `string`): Session cookies for a logged-in account. Required to load the active Stories tray (followed users with a Story right now). From your browser after login, or from Actor `shareze001/instagram-cookies`. ## Actor input object example ```json { "cookies": "sessionid=xxxxxx" } ``` # Actor output Schema ## `dataset` (type: `string`): JSON items: profile rows (user\_id, username, profile\_pic\_url, expiring\_at, latest\_reel\_media) or a single { "message": "..." } object. # 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 = { "cookies": "sessionid=xxxxxx" }; // Run the Actor and wait for it to finish const run = await client.actor("shareze001/instagram-active-story-profiles-by-cookies").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 = { "cookies": "sessionid=xxxxxx" } # Run the Actor and wait for it to finish run = client.actor("shareze001/instagram-active-story-profiles-by-cookies").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 '{ "cookies": "sessionid=xxxxxx" }' | apify call shareze001/instagram-active-story-profiles-by-cookies --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=shareze001/instagram-active-story-profiles-by-cookies", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Active Story Profiles by Cookies", "description": "Uses valid Instagram session cookies to read your active stories tray and list followed accounts that have an active Story right now (not your full following list). Returns username, id, profile picture, and story timing fields. Cookies: browser DevTools or the shareze001/instagram-cookies Actor.", "version": "0.1", "x-build-id": "QlAWz0PfnkDW0wcZM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shareze001~instagram-active-story-profiles-by-cookies/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shareze001-instagram-active-story-profiles-by-cookies", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/shareze001~instagram-active-story-profiles-by-cookies/runs": { "post": { "operationId": "runs-sync-shareze001-instagram-active-story-profiles-by-cookies", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/shareze001~instagram-active-story-profiles-by-cookies/run-sync": { "post": { "operationId": "run-sync-shareze001-instagram-active-story-profiles-by-cookies", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "cookies" ], "properties": { "cookies": { "title": "cookies", "type": "string", "description": "Session cookies for a logged-in account. Required to load the active Stories tray (followed users with a Story right now). From your browser after login, or from Actor `shareze001/instagram-cookies`." } } }, "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 } } } } } } } } } } ```