# Instagram Auto Poster (`fipper_ai/instagram-auto-poster`) Actor Automate your Instagram posts šŸš€ Schedule content, save time, and grow smarter. Perfect for creators, brands, and businesses. ā¬‡ļø Start posting on autopilot - **URL**: https://apify.com/fipper\_ai/instagram-auto-poster.md - **Developed by:** [Josh Baker](https://apify.com/fipper_ai) (community) - **Categories:** Automation, Social media, Integrations - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN 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 ## TikTok Public Scraper Apify Actor for collecting public TikTok metadata from profile, video, hashtag, and search URLs. ### What It Does - accepts TikTok start URLs - renders public pages with Playwright - extracts profile metadata from embedded page state and meta tags - extracts video metadata from oEmbed, embedded page state, and meta tags - discovers public video links on profile, hashtag, and search pages - pushes structured records to the default Apify Dataset - optionally saves screenshots - remembers previous records and marks later results as changed or unchanged ### What It Does Not Do This Actor does not bypass login walls, CAPTCHA, paywalls, region controls, rate limits, private accounts, or access controls. Use it only for public pages you are allowed to collect. ### Input Example ```json { "start_urls": [ { "url": "https://www.tiktok.com/@tiktok" }, { "url": "https://www.tiktok.com/@tiktok/video/7106594312292453678" } ], "max_items": 100, "max_profile_videos": 30, "scroll_rounds": 4, "detect_changes": true, "memory_store_name": "tiktok-public-scraper-memory", "capture_screenshots": false } ```` ### Output Records Records can include: - `type`: `profile`, `video`, `listing`, `summary`, or `error` - `url` - `final_url` - `username` - `display_name` - `description` - `avatar_url` - `video_id` - `author_name` - `thumbnail_url` - `embed_url` - `video_links` - `stats` - `content_hash` - `previous_content_hash` - `changed` - `first_seen_at` - `last_seen_at` - `memory_key` ### Memory Records When `detect_changes` is enabled, the Actor writes each record to the named key-value store: ```text tiktok-public-scraper-memory ``` Each later run compares the new `content_hash` against the remembered record and sets `changed`. ### Local Run ```bash cd /home/007-JB/tiktok-public-scraper python3 main.py ``` On Apify, set input through `INPUT_SCHEMA.json`. # Actor input Schema ## `start_urls` (type: `array`): TikTok profile, video, hashtag, search, or direct short URLs to process. ## `max_items` (type: `integer`): Hard limit for pushed video/profile records. ## `max_profile_videos` (type: `integer`): Maximum video links to collect from each profile, hashtag, or search page. ## `scroll_rounds` (type: `integer`): How many times to scroll profile, hashtag, or search pages to reveal more public video links. ## `wait_ms` (type: `integer`): Extra page wait before extraction. ## `capture_screenshots` (type: `boolean`): Save screenshots of processed pages to the default key-value store. ## `detect_changes` (type: `boolean`): Remember previous records in a key-value store and mark records as changed or unchanged on later runs. ## `memory_store_name` (type: `string`): Named key-value store used to keep previous TikTok records between runs. ## `include_raw_state` (type: `boolean`): Include selected embedded TikTok JSON state keys when found. This can make dataset items larger. ## `user_agent` (type: `string`): Optional user-agent string for normal browser identification. Do not use this to impersonate or bypass controls. ## Actor input object example ```json { "start_urls": [ { "url": "https://www.tiktok.com/@tiktok" } ], "max_items": 100, "max_profile_videos": 30, "scroll_rounds": 4, "wait_ms": 1500, "capture_screenshots": false, "detect_changes": true, "memory_store_name": "tiktok-public-scraper-memory", "include_raw_state": false, "user_agent": "" } ``` # 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 = { "start_urls": [ { "url": "https://www.tiktok.com/@tiktok" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("fipper_ai/instagram-auto-poster").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`šŸ’¾ 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); }); // šŸ“š Want to learn more šŸ“–? Go to ā†’ 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 = { "start_urls": [{ "url": "https://www.tiktok.com/@tiktok" }] } # Run the Actor and wait for it to finish run = client.actor("fipper_ai/instagram-auto-poster").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("šŸ’¾ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # šŸ“š Want to learn more šŸ“–? Go to ā†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "start_urls": [ { "url": "https://www.tiktok.com/@tiktok" } ] }' | apify call fipper_ai/instagram-auto-poster --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fipper_ai/instagram-auto-poster", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Auto Poster", "description": "Automate your Instagram posts šŸš€\nSchedule content, save time, and grow smarter.\nPerfect for creators, brands, and businesses.\nā¬‡ļø Start posting on autopilot", "version": "0.0", "x-build-id": "JqXIzeXCw821adsBz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fipper_ai~instagram-auto-poster/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fipper_ai-instagram-auto-poster", "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/fipper_ai~instagram-auto-poster/runs": { "post": { "operationId": "runs-sync-fipper_ai-instagram-auto-poster", "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/fipper_ai~instagram-auto-poster/run-sync": { "post": { "operationId": "run-sync-fipper_ai-instagram-auto-poster", "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": [ "start_urls" ], "properties": { "start_urls": { "title": "TikTok URLs", "type": "array", "description": "TikTok profile, video, hashtag, search, or direct short URLs to process.", "items": { "type": "object", "properties": { "url": { "title": "URL", "type": "string", "description": "A public TikTok URL.", "editor": "textfield", "pattern": "^https?://.+" } }, "required": [ "url" ], "additionalProperties": false } }, "max_items": { "title": "Max dataset records", "minimum": 1, "type": "integer", "description": "Hard limit for pushed video/profile records.", "default": 100 }, "max_profile_videos": { "title": "Max videos per profile", "minimum": 0, "type": "integer", "description": "Maximum video links to collect from each profile, hashtag, or search page.", "default": 30 }, "scroll_rounds": { "title": "Scroll rounds", "minimum": 0, "maximum": 25, "type": "integer", "description": "How many times to scroll profile, hashtag, or search pages to reveal more public video links.", "default": 4 }, "wait_ms": { "title": "Wait after load", "minimum": 0, "type": "integer", "description": "Extra page wait before extraction.", "default": 1500 }, "capture_screenshots": { "title": "Capture screenshots", "type": "boolean", "description": "Save screenshots of processed pages to the default key-value store.", "default": false }, "detect_changes": { "title": "Keep memory and detect changes", "type": "boolean", "description": "Remember previous records in a key-value store and mark records as changed or unchanged on later runs.", "default": true }, "memory_store_name": { "title": "Memory store name", "type": "string", "description": "Named key-value store used to keep previous TikTok records between runs.", "default": "tiktok-public-scraper-memory" }, "include_raw_state": { "title": "Include raw state", "type": "boolean", "description": "Include selected embedded TikTok JSON state keys when found. This can make dataset items larger.", "default": false }, "user_agent": { "title": "User agent", "type": "string", "description": "Optional user-agent string for normal browser identification. Do not use this to impersonate or bypass controls.", "default": "" } } }, "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 } } } } } } } } } } ```