# Threads Scraper Lite (`igview-owner/threads-scraper-lite`) Actor Threads Scraper Lite: scrape Instagram Threads profiles, bio links, user posts, and user search. Fast Apify Actor with batching and clean JSON output. - **URL**: https://apify.com/igview-owner/threads-scraper-lite.md - **Developed by:** [Sachin Kumar Yadav](https://apify.com/igview-owner) (community) - **Categories:** Social media, Developer tools, Automation - **Stats:** 41 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $7.00 / 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. 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 ## Threads Scraper (Apify) ⚡ High-performance Threads Scraper to collect user profiles (with bio links), user posts, and user search results. Built as an Apify Actor for reliability, batching, and scale. Target keyword: Threads Scraper Related keywords: Instagram Threads scraper, Threads user scraper, Threads posts scraper, Threads API alternative, Threads data extraction, social media intelligence, Threads analytics, Threads crawler. --- ### Table of Contents 📚 - [Features](#features-) - [How it works](#how-it-works-) - [Quick start](#quick-start-) - [Input configuration](#input-configuration-) - [Example inputs](#example-inputs-) - [Example outputs](#example-outputs-) - [Best practices](#best-practices-) - [FAQ](#faq-) - [Changelog](#changelog-) --- ### Features ✨ | Module | What you get | Input switches (single-parameter) | |---------------|-----------------------------------------------|------------------------------------------------------------| | Users info | Profile info by username | `users_enabled`, `fetch_info`, `info_username` | | User posts | Threads/posts by user_id (pk) | `users_enabled`, `fetch_posts`, `posts_user_id` | | Search | Profiles search by username | `search_enabled`, `search_username` | This Threads Scraper is ideal for brand monitoring, creator research, social listening, competitive analysis, and content curation. --- ### How it works 🧠 - **Resilient requests** with lightweight retries and key rotation. - **Buffered writes** to the Apify dataset for performance. - **Modular inputs** so you can enable only what you need. --- ### Quick start ⚡ 1. In your Actor run, provide input JSON using the schema below. 2. Start the Actor. Results are written to the default dataset. --- ### Input configuration ⚙️ | Group | Key | Type | Default | Description | |----------|-------------------|----------|---------|--------------------------------------------------------------| | Users | `users_enabled` | boolean | false | Enable Users module | | | `fetch_info` | boolean | true | Fetch user info via `users/info` | | | `info_username` | string | — | Username (without @) for Users info | | | `fetch_posts` | boolean | true | Fetch user posts via `users/posts` | | | `posts_user_id` | string | — | user_id (pk) from Users info response for fetching posts | | Search | `search_enabled` | boolean | false | Enable Search module | | | `search_username` | string | — | Username to search via `search/profiles` | --- ### Example inputs 📥 - **Fetch user info and posts in one run** ```json { "users_enabled": true, "fetch_info": true, "info_username": "mrbeast", "fetch_posts": true, "posts_user_id": "63634640553" } ```` - **Search profiles by username** ```json { "search_enabled": true, "search_username": "mrbeast" } ``` *** ### Example outputs 📤 - **Raw Users info response** ```json { "status": "Successful", "message": "Data retrieved successfully", "data": { /* user info fields including pk/id, username, etc. */ } } ``` - **Raw Users posts response** ```json { "status": "Successful", "message": "Data retrieved successfully", "data": [ /* array of threads/posts as returned by API */ ] } ``` - **Raw Search profiles response** ```json { "status": "Successful", "message": "Data retrieved successfully", "data": [ /* array of profiles as returned by API */ ] } ``` - **Summary** (final item) ```json { "success": true, "pages_fetched": 3, "total_pushed": 421, "fetched_at": "2025-01-01T12:34:56.000Z", "resultsMeta": { "groups_processed": ["users", "search"] } } ``` *** ### Best practices 🧩 - **Single-parameter per endpoint**: keep inputs minimal (`info_username`, `posts_user_id`, `search_username`). - **Derive posts\_user\_id**: first call Users info to get `pk`/`id`, then set it as `posts_user_id`. - **Multiple fetch in one run**: you can enable both `fetch_info` and `fetch_posts` simultaneously; each uses its own single parameter. *** ### FAQ ❓ - **Is login required?** - No. The Actor uses public data. - **Where do results go?** - The default Apify dataset for the run. *** ### Changelog 📦 - Initial release: Users detail with bio link, User posts, and Users search. *** # Actor input Schema ## `username` (type: `string`): Example: zuck, kyliejenner, mrbeast, or any search keyword. ## `mode` (type: `string`): Choose which endpoint(s) to use for this username/keyword. ## Actor input object example ```json { "username": "zuck", "mode": "detail_and_posts" } ``` # 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": "zuck", "mode": "detail_and_posts" }; // Run the Actor and wait for it to finish const run = await client.actor("igview-owner/threads-scraper-lite").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 = { "username": "zuck", "mode": "detail_and_posts", } # Run the Actor and wait for it to finish run = client.actor("igview-owner/threads-scraper-lite").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 '{ "username": "zuck", "mode": "detail_and_posts" }' | apify call igview-owner/threads-scraper-lite --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=igview-owner/threads-scraper-lite", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Threads Scraper Lite", "description": "Threads Scraper Lite: scrape Instagram Threads profiles, bio links, user posts, and user search. Fast Apify Actor with batching and clean JSON output.", "version": "1.0", "x-build-id": "nVl5x2DjlE47OesLB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/igview-owner~threads-scraper-lite/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-igview-owner-threads-scraper-lite", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/igview-owner~threads-scraper-lite/runs": { "post": { "operationId": "runs-sync-igview-owner-threads-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/igview-owner~threads-scraper-lite/run-sync": { "post": { "operationId": "run-sync-igview-owner-threads-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "mode" ], "properties": { "username": { "title": "Username / Keyword", "type": "string", "description": "Example: zuck, kyliejenner, mrbeast, or any search keyword." }, "mode": { "title": "What do you want to fetch?", "enum": [ "user_detail", "detail_and_posts", "posts_search", "users_search" ], "type": "string", "description": "Choose which endpoint(s) to use for this username/keyword." } } }, "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 } } } } } } } } } } ```