# Bluesky Influencer & Audience Intelligence (`straightforward_hydra/bluesky-influencer-intelligence`) Actor Discover & rank top Bluesky accounts in any niche, enrich profiles, scrape posts & engagement, export followers. No key. - **URL**: https://apify.com/straightforward\_hydra/bluesky-influencer-intelligence.md - **Developed by:** [Dev D](https://apify.com/straightforward_hydra) (community) - **Categories:** Social media, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 items 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 Influencer & Audience Intelligence 🦋 **Discover and rank the top Bluesky accounts in any niche, enrich profiles, scrape posts & engagement, and export followers — from Bluesky's public API. No API key, no proxy.** Bluesky is the fastest-growing open social network — and it's still early. This actor is your **early-mover intelligence** for it: - 🔥 **Discover niche influencers** — give it a topic (`crypto`, `AI`, `climate`, `journalism`) and get a **ranked list of the top accounts** by followers, each with an **engagement score** (avg likes/reposts/replies). - 👤 **Profile enrichment** — turn a list of handles into full profiles (followers, following, post count, bio). - 📝 **Posts & engagement** — an account's recent posts with like/repost/reply/quote counts. - 👥 **Follower export** — export any account's followers for audience analysis or outreach. Perfect for **influencer marketing, brand & competitor monitoring, audience research, PR and social analytics** — on the platform before it's saturated. > Uses Bluesky's public **AT Protocol** AppView — no key, no login, pure JSON. Very low maintenance. --- ### Modes - 🔥 **Discover** — niche keyword → ranked top accounts (+ optional engagement). - 👤 **Profiles** — handles → enriched profiles. - 📝 **Posts** — handles → recent posts with engagement. - 👥 **Followers** — handle → follower export. ### Features - ✅ **No API key, no proxy** — official public AT Protocol API. - ✅ **Follower + engagement ranking** — find who's big *and* who's actually engaging. - ✅ **Early-mover** — analytics for a platform most tools don't cover yet. - ✅ **Clean JSON** — no HTML scraping, low maintenance. --- ### Input | Field | Description | |---|---| | **Mode** | discover / profiles / posts / followers. | | **Query** | Niche keyword (discover mode). | | **Handles** | Handles for profiles / posts / followers modes. | | **Include engagement** | Sample recent posts to compute avg likes/reposts + score. | | **Engagement sample size** | Posts sampled for engagement. | | **Max results** | discover: top N accounts; posts/followers: max per handle. | #### Example — top AI accounts, ranked, with engagement ```json { "mode": "discover", "query": "AI", "includeEngagement": true, "maxResults": 100 } ```` #### Example — export an account's followers ```json { "mode": "followers", "handles": ["bsky.app"], "maxResults": 5000 } ``` #### Example — a brand's posts & engagement ```json { "mode": "posts", "handles": ["nbcnews.com"], "maxResults": 100 } ``` ### Output (discover) ```json { "rank": 1, "handle": "cryptosniper.bsky.social", "display_name": "Crypto Sniper", "followers_count": 21537, "follows_count": 300, "posts_count": 4793, "description": "…", "matched_query": "crypto", "avg_likes": 3270.1, "avg_reposts": 900.2, "avg_replies": 148.4, "engagement_score": 4318.7, "sampled_posts": 15, "url": "https://bsky.app/profile/cryptosniper.bsky.social" } ``` Posts mode returns post text + like/repost/reply/quote counts; followers mode returns handle/DID/name per follower. ### Run it on a schedule Re-run discovery weekly to watch a niche's leaderboard shift, or track an account's follower growth and engagement over time — pipe to a sheet, database or webhook. ### Notes & limitations - Uses the **public** AppView — full-text post search requires auth, so discovery is by **account** (the higher-value angle). Everything here works with no key. - Ranking is over the accounts surfaced by Bluesky's actor search for your keyword, enriched with real follower counts. - Data source: Bluesky / AT Protocol. *** #### Keywords Bluesky, AT Protocol, influencer marketing, social media, influencer discovery, follower export, engagement, social analytics, audience research, brand monitoring, creator analytics, social listening, bsky, emerging social media, profile scraper, followers scraper, social intelligence, Twitter alternative. # Actor input Schema ## `mode` (type: `string`): discover = find & rank top accounts in a niche; profiles = enrich handles; posts = an account's posts + engagement; followers = export followers. ## `query` (type: `string`): Topic/niche to find top accounts for, e.g. "crypto", "AI", "climate", "journalism". ## `handles` (type: `array`): Bluesky handles, e.g. \["bsky.app", "nbcnews.com"]. The @ is optional. ## `includeEngagement` (type: `boolean`): For discover/profiles: sample recent posts to compute average likes/reposts/replies and an engagement score. Adds one call per account. ## `engagementSampleSize` (type: `integer`): How many recent posts to sample when computing engagement. ## `maxResults` (type: `integer`): discover: number of top accounts to return. posts/followers: max per handle. ## Actor input object example ```json { "mode": "discover", "query": "AI", "includeEngagement": false, "engagementSampleSize": 20, "maxResults": 100 } ``` # 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 = { "query": "AI" }; // Run the Actor and wait for it to finish const run = await client.actor("straightforward_hydra/bluesky-influencer-intelligence").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 = { "query": "AI" } # Run the Actor and wait for it to finish run = client.actor("straightforward_hydra/bluesky-influencer-intelligence").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 '{ "query": "AI" }' | apify call straightforward_hydra/bluesky-influencer-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=straightforward_hydra/bluesky-influencer-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bluesky Influencer & Audience Intelligence", "description": "Discover & rank top Bluesky accounts in any niche, enrich profiles, scrape posts & engagement, export followers. No key.", "version": "0.1", "x-build-id": "6zE8NaOkI7h401Ctc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/straightforward_hydra~bluesky-influencer-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-straightforward_hydra-bluesky-influencer-intelligence", "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/straightforward_hydra~bluesky-influencer-intelligence/runs": { "post": { "operationId": "runs-sync-straightforward_hydra-bluesky-influencer-intelligence", "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/straightforward_hydra~bluesky-influencer-intelligence/run-sync": { "post": { "operationId": "run-sync-straightforward_hydra-bluesky-influencer-intelligence", "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": { "mode": { "title": "Mode", "enum": [ "discover", "profiles", "posts", "followers" ], "type": "string", "description": "discover = find & rank top accounts in a niche; profiles = enrich handles; posts = an account's posts + engagement; followers = export followers.", "default": "discover" }, "query": { "title": "Niche keyword (discover mode)", "type": "string", "description": "Topic/niche to find top accounts for, e.g. \"crypto\", \"AI\", \"climate\", \"journalism\"." }, "handles": { "title": "Handles (profiles / posts / followers modes)", "type": "array", "description": "Bluesky handles, e.g. [\"bsky.app\", \"nbcnews.com\"]. The @ is optional.", "items": { "type": "string" } }, "includeEngagement": { "title": "Include engagement", "type": "boolean", "description": "For discover/profiles: sample recent posts to compute average likes/reposts/replies and an engagement score. Adds one call per account.", "default": false }, "engagementSampleSize": { "title": "Engagement sample size", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many recent posts to sample when computing engagement.", "default": 20 }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 100000, "type": "integer", "description": "discover: number of top accounts to return. posts/followers: max per handle.", "default": 100 } } }, "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 } } } } } } } } } } ```