# Bluesky Scraper — Posts, Profiles & Followers (`hipersoft/bluesky-scraper`) Actor Scrape Bluesky posts, profiles and social graph: a user's posts (text, likes, reposts, replies), profile stats, followers and following. Search users by keyword. Clean public API, no login or key. - **URL**: https://apify.com/hipersoft/bluesky-scraper.md - **Developed by:** [hiper soft](https://apify.com/hipersoft) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.0008 / item scraped 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Bluesky Scraper — Posts, Profiles, Followers & Keyword User Search Pull public data straight from Bluesky: a user's posts with full engagement counts, profile stats, and their followers and following lists — all as clean structured JSON. Feed it handles, DIDs, or profile URLs (or discover users by keyword), pick a data type, and get back tidy records ready for analysis. No account, no API key. Built for social researchers, growth teams, journalists, and anyone tracking the Bluesky network. ### Features - 🦋 **Four data types in one Actor** — switch `dataType` between posts, profile info, followers, and following. - 🔎 **Discover users by keyword** — `searchTerms` finds matching accounts via actor search and scrapes them alongside your `actors` list. - 📊 **Real engagement metrics** — every post carries `likeCount`, `repostCount`, `replyCount`, `quoteCount`, and `bookmarkCount`. - 🖼️ **Media and link cards** — extracts post `images`, plus `externalUrl`, `externalTitle`, and `externalDescription` from embedded link previews. - 🔁 **Repost & reply flags** — `isRepost` and `isReply` mark timeline context; posts are de-duplicated across feeds automatically. - 🎯 **Flexible inputs** — accepts handles (`nytimes.com`), DIDs, or full `bsky.app/profile/...` URLs interchangeably. - 📈 **Scales to 20,000 items per user** with cursor-based pagination under the hood. ### What you get Each post is one clean JSON record: ```json { "type": "post", "uri": "at://did:plc:abc123/app.bsky.feed.post/3kxyz", "handle": "nytimes.com", "displayName": "The New York Times", "authorDid": "did:plc:abc123", "text": "Breaking: ...", "createdAt": "2026-07-20T14:03:00.000Z", "langs": ["en"], "likeCount": 812, "repostCount": 145, "replyCount": 63, "quoteCount": 21, "bookmarkCount": 9, "isReply": false, "isRepost": false, "embedType": "app.bsky.embed.images#view", "images": ["https://cdn.bsky.app/img/feed_fullsize/plain/..."], "externalUrl": null, "externalTitle": null, "externalDescription": null, "url": "https://bsky.app/profile/nytimes.com/post/3kxyz" } ```` ### Input ```json { "actors": ["jay.bsky.team", "https://bsky.app/profile/nytimes.com"], "searchTerms": ["climate news"], "dataType": "posts", "maxItemsPerActor": 100, "maxSearchActors": 25 } ``` | Field | Description | | --- | --- | | `actors` | Handles, DIDs, or profile URLs to scrape. | | `searchTerms` | Keywords; matching users are found and scraped too. | | `dataType` | `posts`, `profile`, `followers`, or `following`. | | `maxItemsPerActor` | Max posts/followers/following per user (up to 20000). | | `maxSearchActors` | How many users to take from each search term. | ### Use cases - Track engagement on a brand or competitor's Bluesky posts over time. - Build follower/following graphs for network and influencer analysis. - Discover accounts in a topic niche via keyword search, then pull their feeds. - Monitor news outlets and public figures for social listening dashboards. ### Pricing Pay-per-event: you're billed a small amount per run and per item scraped — you only pay for what you get. See the **Pricing** tab for current rates. ### Notes This Actor uses Bluesky's public AppView API (public.api.bsky.app) and reads only public, unauthenticated data — no login or key required. It is an independent tool and is not affiliated with, endorsed by, or connected to Bluesky Social PBC. # Actor input Schema ## `actors` (type: `array`): Bluesky handles (e.g. bsky.app), DIDs, or profile URLs. The selected data type is scraped for each. ## `searchTerms` (type: `array`): Optional. Find users matching these keywords (via actor search) and include them alongside the handles above. ## `dataType` (type: `string`): What to scrape for each user. ## `maxItemsPerActor` (type: `integer`): Maximum posts / followers / following to collect per user (ignored for profile info). ## `maxSearchActors` (type: `integer`): How many users to take from each search term. ## Actor input object example ```json { "actors": [ "jay.bsky.team", "https://bsky.app/profile/nytimes.com" ], "searchTerms": [ "climate news" ], "dataType": "posts", "maxItemsPerActor": 100, "maxSearchActors": 25 } ``` # 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 = { "actors": [ "bsky.app" ] }; // Run the Actor and wait for it to finish const run = await client.actor("hipersoft/bluesky-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 = { "actors": ["bsky.app"] } # Run the Actor and wait for it to finish run = client.actor("hipersoft/bluesky-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 '{ "actors": [ "bsky.app" ] }' | apify call hipersoft/bluesky-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hipersoft/bluesky-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bluesky Scraper — Posts, Profiles & Followers", "description": "Scrape Bluesky posts, profiles and social graph: a user's posts (text, likes, reposts, replies), profile stats, followers and following. Search users by keyword. Clean public API, no login or key.", "version": "1.0", "x-build-id": "UQAC5wNHd4GBRh78g" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hipersoft~bluesky-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hipersoft-bluesky-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hipersoft~bluesky-scraper/runs": { "post": { "operationId": "runs-sync-hipersoft-bluesky-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hipersoft~bluesky-scraper/run-sync": { "post": { "operationId": "run-sync-hipersoft-bluesky-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "actors": { "title": "Handles / profile URLs", "type": "array", "description": "Bluesky handles (e.g. bsky.app), DIDs, or profile URLs. The selected data type is scraped for each.", "items": { "type": "string" } }, "searchTerms": { "title": "Search users by keyword", "type": "array", "description": "Optional. Find users matching these keywords (via actor search) and include them alongside the handles above.", "items": { "type": "string" } }, "dataType": { "title": "Data type", "enum": [ "posts", "profile", "followers", "following" ], "type": "string", "description": "What to scrape for each user.", "default": "posts" }, "maxItemsPerActor": { "title": "Max items per user", "minimum": 1, "maximum": 20000, "type": "integer", "description": "Maximum posts / followers / following to collect per user (ignored for profile info).", "default": 100 }, "maxSearchActors": { "title": "Max users per search term", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many users to take from each search term.", "default": 25 } } }, "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 } } } } } } } } } } ```