# LinkedIn Posts Search Scraper — Public Posts (`crabwalker/linkedin-posts-search-scraper`) Actor Search and extract public LinkedIn posts, authors, timestamps, reactions, comments, and media into structured datasets. - **URL**: https://apify.com/crabwalker/linkedin-posts-search-scraper.md - **Developed by:** [Crab Walker](https://apify.com/crabwalker) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 linkedin posts 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/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 ## LinkedIn Public Posts Search Scraper Search public LinkedIn posts by keyword without login or cookies. The Actor is limited to public search pages and does not access authenticated profiles. ### Input Use the reference Actor fields `keyword`, `sort_type`, `page_number`, `date_filter`, `limit`, and the optional URN/job-title filters. `startUrls` and the legacy aliases `searchTerms`, `sort`, and `maxItems` are also accepted. ### Output Each row exposes the reference LinkedIn fields (`postId`, `postUrl`, `authorName`, `authorProfileUrl`, `authorHeadline`, `postedAt`, `content`, `mediaType`, `reactionsCount`, `commentsCount`, and `searchKeyword`) plus the shared provenance fields used by the other scrapers. Add an `APIFY_API_TOKEN` repository secret. The GitHub Actions workflow runs tests and publishes the Actor on pushes to `main` or `master`. # Actor input Schema ## `keyword` (type: `string`): Keyword or phrase to search in public LinkedIn posts. ## `sort_type` (type: `string`): Sort results by relevance or date posted. ## `page_number` (type: `integer`): One-based LinkedIn search result page to start from. ## `date_filter` (type: `string`): Restrict results to a recent time window. ## `limit` (type: `integer`): Maximum number of posts to return per search. ## `company_urns` (type: `string`): Optional comma-separated company URNs to filter posts. ## `author_company_urns` (type: `string`): Optional comma-separated author company URNs. ## `author_industry_urns` (type: `string`): Optional comma-separated author industry URNs. ## `author_job_title` (type: `string`): Optional author job title filter. ## `member_urns` (type: `string`): Optional comma-separated member URNs to filter authors. ## `total_posts` (type: `integer`): Maximum total posts to collect across searches. ## `startUrls` (type: `array`): Optional public LinkedIn content-search URLs. ## `requestDelaySecs` (type: `number`): Seconds to wait between LinkedIn page requests. ## `proxyConfiguration` (type: `object`): Optional Apify proxy configuration for requests. ## Actor input object example ```json { "keyword": "", "sort_type": "relevance", "page_number": 1, "date_filter": "", "limit": 50, "company_urns": "", "author_company_urns": "", "author_industry_urns": "", "author_job_title": "", "member_urns": "", "startUrls": [], "requestDelaySecs": 2, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ```` # Actor output Schema ## `dataset` (type: `string`): No description # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("crabwalker/linkedin-posts-search-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 = {} # Run the Actor and wait for it to finish run = client.actor("crabwalker/linkedin-posts-search-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 '{}' | apify call crabwalker/linkedin-posts-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crabwalker/linkedin-posts-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Posts Search Scraper — Public Posts", "description": "Search and extract public LinkedIn posts, authors, timestamps, reactions, comments, and media into structured datasets.", "version": "1.0", "x-build-id": "Przl656hD0BhCcEay" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crabwalker~linkedin-posts-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crabwalker-linkedin-posts-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crabwalker~linkedin-posts-search-scraper/runs": { "post": { "operationId": "runs-sync-crabwalker-linkedin-posts-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crabwalker~linkedin-posts-search-scraper/run-sync": { "post": { "operationId": "run-sync-crabwalker-linkedin-posts-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keyword": { "title": "Search Keyword", "type": "string", "description": "Keyword or phrase to search in public LinkedIn posts.", "default": "" }, "sort_type": { "title": "Sort Type", "enum": [ "relevance", "date_posted" ], "type": "string", "description": "Sort results by relevance or date posted.", "default": "relevance" }, "page_number": { "title": "Page Number", "minimum": 1, "type": "integer", "description": "One-based LinkedIn search result page to start from.", "default": 1 }, "date_filter": { "title": "Date Filter", "enum": [ "", "past-1h", "past-24h", "past-week", "past-month" ], "type": "string", "description": "Restrict results to a recent time window.", "default": "" }, "limit": { "title": "Result limit", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of posts to return per search.", "default": 50 }, "company_urns": { "title": "Company URNs", "type": "string", "description": "Optional comma-separated company URNs to filter posts.", "default": "" }, "author_company_urns": { "title": "Author Company URNs", "type": "string", "description": "Optional comma-separated author company URNs.", "default": "" }, "author_industry_urns": { "title": "Author Industry URNs", "type": "string", "description": "Optional comma-separated author industry URNs.", "default": "" }, "author_job_title": { "title": "Author Job Title", "type": "string", "description": "Optional author job title filter.", "default": "" }, "member_urns": { "title": "Member URNs", "type": "string", "description": "Optional comma-separated member URNs to filter authors.", "default": "" }, "total_posts": { "title": "Total Posts to Scrape", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum total posts to collect across searches." }, "startUrls": { "title": "LinkedIn search URLs", "type": "array", "description": "Optional public LinkedIn content-search URLs.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "requestDelaySecs": { "title": "Delay between pages", "minimum": 0, "maximum": 30, "type": "number", "description": "Seconds to wait between LinkedIn page requests.", "default": 2 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify proxy configuration for requests.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```