# LinkedIn Profile Posts Export (`automationagents/linkedin-profile-posts-export`) Actor Export posts from a LinkedIn profile using an authenticated session. - **URL**: https://apify.com/automationagents/linkedin-profile-posts-export.md - **Developed by:** [Alex Jordan](https://apify.com/automationagents) (community) - **Categories:** Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ### What does LinkedIn Profile Posts Export do? **LinkedIn Profile Posts Export** extracts posts from a LinkedIn profile using an authenticated session. It is useful for creator research, profile monitoring, and content intelligence workflows. Built on the **Apify platform**, this Actor supports scheduling, webhooks, and dataset exports. ### Why use LinkedIn Profile Posts Export? - **Profile monitoring** - Export posts from a target LinkedIn profile - **Content intelligence** - Review recent profile activity in structured form - **Workflow automation** - Send post data into dashboards, sheets, or internal pipelines ### How to use LinkedIn Profile Posts Export 1. Open the Actor on Apify 2. Enter the LinkedIn profile URL and authenticated session fields 3. Start the run 4. Review the dataset output ### Input This Actor accepts the fields required to extract posts from a LinkedIn profile with an authenticated session. #### Proxy object Use the `proxy` object to define how requests should be routed. Common fields are: - `ip` - Proxy host or endpoint URL - `port` - Proxy port - `username` - Proxy username - `password` - Proxy password **Example input:** ```json { "liProfileUrl": "https://www.linkedin.com/in/example-profile/", "maxCount": 50, "li_at": "AQEDAR_EXAMPLE_SESSION_TOKEN", "JSESSIONID": "ajax:1234567890123456789", "bcookie": "v=2&example-browser-cookie", "bscookie": "v=1&example-secure-browser-cookie", "csrf-token": "ajax:1234567890123456789", "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/145.0.0.0 Safari/537.36", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self-profile/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "user_example|session_demo", "password": "example_proxy_password" } } ```` ### Output The Actor writes the collected LinkedIn profile posts to the default dataset. **Example output:** ```json { "success": true, "response": [ { "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:1234567890123456789/", "postText": "Sharing a workflow update from this week.", "postedAt": "2026-06-24T08:00:00.000Z", "timestamp": "2026-06-25T08:00:00.000Z" } ] } ``` ### Pricing / Cost estimation **$0.0025 per started block of up to 50 results** on Apify. - `1-50` results: `$0.0025` - `51-100` results: `$0.0050` - `101-150` results: `$0.0075` No result means no result-charge event. ### Support If you need adjustments for your workflow, use the Actor Issues tab or your internal support channel. # Actor input Schema ## `liProfileUrl` (type: `string`): liProfileUrl ## `maxCount` (type: `number`): maxCount ## `li_at` (type: `string`): li\_at ## `JSESSIONID` (type: `string`): JSESSIONID ## `bcookie` (type: `string`): bcookie ## `liap` (type: `string`): liap ## `li_theme_set` (type: `string`): li\_theme\_set ## `li_theme` (type: `string`): li\_theme ## `timezone` (type: `string`): timezone ## `bscookie` (type: `string`): bscookie ## `user-agent` (type: `string`): user-agent ## `timezoneOffset` (type: `string`): timezoneOffset ## `csrf-token` (type: `string`): csrf-token ## `profileId` (type: `string`): profileId ## `User-Agent` (type: `string`): User-Agent ## `x-li-track` (type: `string`): x-li-track ## `x-li-lang` (type: `string`): x-li-lang ## `X-Restli-Protocol-Version` (type: `string`): X-Restli-Protocol-Version ## `txSmSelfProfileUrl` (type: `string`): txSmSelfProfileUrl ## `proxy` (type: `object`): proxy ## Actor input object example ```json {} ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("automationagents/linkedin-profile-posts-export").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("automationagents/linkedin-profile-posts-export").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 automationagents/linkedin-profile-posts-export --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automationagents/linkedin-profile-posts-export", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Profile Posts Export", "description": "Export posts from a LinkedIn profile using an authenticated session.", "version": "0.4", "x-build-id": "kfzwxHaqThSmh0fgz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automationagents~linkedin-profile-posts-export/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automationagents-linkedin-profile-posts-export", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automationagents~linkedin-profile-posts-export/runs": { "post": { "operationId": "runs-sync-automationagents-linkedin-profile-posts-export", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automationagents~linkedin-profile-posts-export/run-sync": { "post": { "operationId": "run-sync-automationagents-linkedin-profile-posts-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "JSESSIONID", "User-Agent", "X-Restli-Protocol-Version", "bcookie", "bscookie", "csrf-token", "liProfileUrl", "li_at", "li_theme", "li_theme_set", "liap", "maxCount", "profileId", "proxy", "timezone", "timezoneOffset", "txSmSelfProfileUrl", "user-agent", "x-li-lang", "x-li-track" ], "properties": { "liProfileUrl": { "title": "liProfileUrl", "type": "string", "description": "liProfileUrl" }, "maxCount": { "title": "maxCount", "type": "number", "description": "maxCount" }, "li_at": { "title": "li_at", "type": "string", "description": "li_at" }, "JSESSIONID": { "title": "JSESSIONID", "type": "string", "description": "JSESSIONID" }, "bcookie": { "title": "bcookie", "type": "string", "description": "bcookie" }, "liap": { "title": "liap", "type": "string", "description": "liap" }, "li_theme_set": { "title": "li_theme_set", "type": "string", "description": "li_theme_set" }, "li_theme": { "title": "li_theme", "type": "string", "description": "li_theme" }, "timezone": { "title": "timezone", "type": "string", "description": "timezone" }, "bscookie": { "title": "bscookie", "type": "string", "description": "bscookie" }, "user-agent": { "title": "user-agent", "type": "string", "description": "user-agent" }, "timezoneOffset": { "title": "timezoneOffset", "type": "string", "description": "timezoneOffset" }, "csrf-token": { "title": "csrf-token", "type": "string", "description": "csrf-token" }, "profileId": { "title": "profileId", "type": "string", "description": "profileId" }, "User-Agent": { "title": "User-Agent", "type": "string", "description": "User-Agent" }, "x-li-track": { "title": "x-li-track", "type": "string", "description": "x-li-track" }, "x-li-lang": { "title": "x-li-lang", "type": "string", "description": "x-li-lang" }, "X-Restli-Protocol-Version": { "title": "X-Restli-Protocol-Version", "type": "string", "description": "X-Restli-Protocol-Version" }, "txSmSelfProfileUrl": { "title": "txSmSelfProfileUrl", "type": "string", "description": "txSmSelfProfileUrl" }, "proxy": { "title": "proxy", "type": "object", "description": "proxy" } } }, "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 } } } } } } } } } } ```