# LinkedIn Posts by Keywords (No Cookies) (`data_pool/linkedin-post-scraper`) Actor Crawl LinkedIn posts by keywords. No login or cookies required. - **URL**: https://apify.com/data\_pool/linkedin-post-scraper.md - **Developed by:** [Data Pool](https://apify.com/data_pool) (community) - **Categories:** Social media, Lead generation, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.50 / 1,000 post scrapeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Post Keyword Scraper — No Cookies, No Login Search **LinkedIn posts by keyword** and get clean, structured results — **without connecting your LinkedIn account, logging in, or pasting any cookies**. Just enter keywords and run. ### What you get For every matching post: - **Author** — name, headline, profile URL, and whether it's a person or company - **Post text** and a direct **permalink** - **Timestamp** the post was published - **Engagement** — reactions, comments, reposts, and impressions (when available) - **Media** attached to the post (images, documents, videos) - The **keyword** each post matched Results are **de-duplicated** within a run, so a post matching two of your keywords appears once. ### Input | Field | Description | |---|---| | **Keywords** (required) | One or more search terms. The Actor runs a separate LinkedIn post search per term. Each term must be 85 characters or fewer. | | **Max posts per keyword** | How many posts to return per keyword. Use `0` for as many as LinkedIn surfaces (realistically a few hundred per search). Default `100`. | | **Sort by** | *Top match (relevance)* or *Latest (date posted)*. | | **Date posted** | Limit to *Past 24 hours*, *Past week*, or *Past month*. Default: any time. | #### Example input ```json { "keywords": ["generative ai", "b2b sales"], "maxItems": 25, "sortBy": "date_posted", "datePosted": "week" } ```` ### Output Each post is one dataset item you can export to JSON, CSV, Excel, or pull via the API: ```json { "postUrl": "https://www.linkedin.com/posts/jane-doe_activity-7212...", "text": "Excited to share how our team closed the quarter…", "postedAtIso": "2026-07-01T12:00:00Z", "author": { "name": "Jane Doe", "headline": "VP Sales @ Acme", "profileUrl": "https://www.linkedin.com/in/jane-doe", "type": "person" }, "stats": { "reactions": 340, "comments": 25, "reposts": 12, "impressions": 9000 }, "media": [ { "type": "image", "url": "https://…" } ], "isRepost": false, "matchedKeyword": "b2b sales" } ``` ### Common uses - **Lead generation** — surface people and companies posting about your market. - **Social listening** — track how a topic, product, or brand is discussed. - **Content research** — find the best-performing posts on a theme by engagement. - **Market & competitor monitoring** — follow keyword-driven conversations over time. ### Pricing **$1.50 per 1,000 posts — that's it.** No subscription, no per-run fee, no charge for posts you don't receive. You can set a maximum spend per run so costs stay predictable. ### Notes - Please use scraped data responsibly and in line with applicable laws (including data-protection rules such as GDPR) and LinkedIn's terms. You are responsible for having a lawful basis to collect and process the data you request. - LinkedIn search results can vary between runs, and result availability depends on what LinkedIn surfaces for a given keyword at the time of the run. # Actor input Schema ## `keywords` (type: `array`): Search terms. One LinkedIn post search runs per term. Each term must be 85 characters or fewer (LinkedIn's limit). ## `maxItems` (type: `integer`): Maximum number of posts to return per keyword. Use 0 for as many as the source allows (LinkedIn realistically surfaces a few hundred per search). ## `sortBy` (type: `string`): Order results by relevance (Top match) or most recent. ## `datePosted` (type: `string`): Only return posts from this time window. Leave as 'Any time' for no date filter. ## `source` (type: `string`): Backend used to fetch posts. 'Managed pool' (default) uses our LinkedIn account pool — no cookies needed. 'My LinkedIn cookie' is planned and not yet available. ## `linkedinCookie` (type: `string`): Only used when Data source = 'My LinkedIn cookie'. Paste your li\_at session cookie. WARNING: using your own cookie can get your LinkedIn account restricted or banned and violates LinkedIn's User Agreement. Prefer a secondary account. Stored encrypted, never logged. ## `proxyConfiguration` (type: `object`): Proxy used only for the user-cookie path. The managed pool supplies its own per-account proxies. ## Actor input object example ```json { "keywords": [ "b2b sales", "product management" ], "maxItems": 100, "sortBy": "relevance", "datePosted": "", "source": "managed_pool", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `posts` (type: `string`): The LinkedIn posts matched by your keywords, one item per post. # 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 = { "keywords": [ "generative ai" ] }; // Run the Actor and wait for it to finish const run = await client.actor("data_pool/linkedin-post-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 = { "keywords": ["generative ai"] } # Run the Actor and wait for it to finish run = client.actor("data_pool/linkedin-post-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 '{ "keywords": [ "generative ai" ] }' | apify call data_pool/linkedin-post-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_pool/linkedin-post-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Posts by Keywords (No Cookies)", "description": "Crawl LinkedIn posts by keywords. No login or cookies required.", "version": "0.1", "x-build-id": "RzG4odKLnP9PnBUea" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_pool~linkedin-post-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_pool-linkedin-post-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_pool~linkedin-post-scraper/runs": { "post": { "operationId": "runs-sync-data_pool-linkedin-post-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_pool~linkedin-post-scraper/run-sync": { "post": { "operationId": "run-sync-data_pool-linkedin-post-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Search terms. One LinkedIn post search runs per term. Each term must be 85 characters or fewer (LinkedIn's limit).", "items": { "type": "string" } }, "maxItems": { "title": "Max posts per keyword", "minimum": 0, "type": "integer", "description": "Maximum number of posts to return per keyword. Use 0 for as many as the source allows (LinkedIn realistically surfaces a few hundred per search).", "default": 100 }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "date_posted" ], "type": "string", "description": "Order results by relevance (Top match) or most recent.", "default": "relevance" }, "datePosted": { "title": "Date posted", "enum": [ "", "24h", "week", "month" ], "type": "string", "description": "Only return posts from this time window. Leave as 'Any time' for no date filter.", "default": "" }, "source": { "title": "Data source", "enum": [ "managed_pool", "user_cookie" ], "type": "string", "description": "Backend used to fetch posts. 'Managed pool' (default) uses our LinkedIn account pool — no cookies needed. 'My LinkedIn cookie' is planned and not yet available.", "default": "managed_pool" }, "linkedinCookie": { "title": "Your LinkedIn li_at cookie (advanced, optional)", "type": "string", "description": "Only used when Data source = 'My LinkedIn cookie'. Paste your li_at session cookie. WARNING: using your own cookie can get your LinkedIn account restricted or banned and violates LinkedIn's User Agreement. Prefer a secondary account. Stored encrypted, never logged." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy used only for the user-cookie path. The managed pool supplies its own per-account proxies.", "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 } } } } } } } } } } ```