# Linkedin Profile Poster (`bhansalisoft/linkedin-profile-poster`) Actor Linkedin Profile Poster - is unique to auto post to Linkedin feed with unique message selection from multiple messages. you can schedule this tool daily with unique message. - **URL**: https://apify.com/bhansalisoft/linkedin-profile-poster.md - **Developed by:** [bhansalisoft](https://apify.com/bhansalisoft) (community) - **Categories:** Automation, Lead generation, Social media - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $20.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ### Linkedin Profile Poster API Linkedin Profile Poster - is unique to auto post to Linkedin feed with unique message selection from multiple messages. you can schedule this tool daily with unique message. - ✅ Software will post to Linkedin profile feed. - ✅ Software will show you status log whether posting is success or not. - ✅ Software with extract data with very securily so that linkedin not block you. - ✅ Software with extractraction speed is in 1 second 100 data. - ✅ 100% Real Time Extract information with Advance Export into Excel ,CSV and Text Format. ### How to use Search Using below parameter. - Linkedin Group URL : Enter your list of Linkedin Group urls like [ "https://www.linkedin.com/groups/2153908/","https://www.linkedin.com/groups/2153908/"]. you must have join group before extract members - Enter Your Message : You can insert multiple message in json format [ "Message 1","Message 2"]. our tool will choose random one message and send. so you can schedule tool with multiple message add in this. - Cookies : Insert Linkedin Cookies - Click on Save and Start Button for Start Process of Linkedin Group auto poster. ### How to get Linkedin Cookies 1. ✅ Step 1 : Install Chrome Extension [Export cookie JSON file for Puppeteer](https://chromewebstore.google.com/detail/export-cookie-json-file-f/nmckokihipjgplolmcmjakknndddifde/reviews) in chrome browser 2. ✅ Step 2 : Login to your Linkedin 3. ✅ Step 3 : After login, open chrome Extension "[Export cookie JSON file for Puppeteer" and Click Export icon, it will download Cookie file..copy cookie from file 4. ✅ Step 4 : Go to Software input Area,Paste Cookie on Box "Linkedin Cookie" Demo video For Get Cookie from any website https://youtu.be/yYJ6l2jm83Q ### check software demo https://youtu.be/awh4T2xNoK0 if you face any issue , you can email us at bhansalisoft781986@gmail.com # Actor input Schema ## `Message` (type: `array`): Enter Your Message List(We will select rendom unique message from list) ## `Cookies` (type: `array`): Insert Linkedin Cookie, please check product information how to get cookie ## Actor input object example ```json { "Message": [ "Test message 1", "Test message 2" ] } ```` # 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 = { "Message": [ "Test message 1", "Test message 2" ] }; // Run the Actor and wait for it to finish const run = await client.actor("bhansalisoft/linkedin-profile-poster").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 = { "Message": [ "Test message 1", "Test message 2", ] } # Run the Actor and wait for it to finish run = client.actor("bhansalisoft/linkedin-profile-poster").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 '{ "Message": [ "Test message 1", "Test message 2" ] }' | apify call bhansalisoft/linkedin-profile-poster --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bhansalisoft/linkedin-profile-poster", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profile Poster", "description": "Linkedin Profile Poster - is unique to auto post to Linkedin feed with unique message selection from multiple messages. you can schedule this tool daily with unique message.", "version": "0.0", "x-build-id": "EcBdFqJeCswrwDjeN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bhansalisoft~linkedin-profile-poster/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bhansalisoft-linkedin-profile-poster", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/bhansalisoft~linkedin-profile-poster/runs": { "post": { "operationId": "runs-sync-bhansalisoft-linkedin-profile-poster", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/bhansalisoft~linkedin-profile-poster/run-sync": { "post": { "operationId": "run-sync-bhansalisoft-linkedin-profile-poster", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "Message", "Cookies" ], "properties": { "Message": { "title": "Enter Your Message List(We will select rendom unique message from list)", "type": "array", "description": "Enter Your Message List(We will select rendom unique message from list)" }, "Cookies": { "title": "Linkedin Cookie:please check product information how to get cookie", "type": "array", "description": "Insert Linkedin Cookie, please check product information how to get cookie" } } }, "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 } } } } } } } } } } ```