# LinkedIn Jobs Scraper (`nomad-dev/linkedin-scraper`) Actor Collect recent job postings from LinkedIn's public job search by keyword and location. Returns structured records with title, company, location, URL and optional full description. No account or login required. - **URL**: https://apify.com/nomad-dev/linkedin-scraper.md - **Developed by:** [Nomad.Dev](https://apify.com/nomad-dev) (community) - **Categories:** Jobs - **Stats:** 2 total users, 0 monthly users, 100.0% 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 ## LinkedIn Jobs Scraper Search LinkedIn job postings by keyword and location and get clean, structured data — **no account, no login, no setup required**. Monitor recent openings across any keyword, role or location, export to JSON/CSV/Excel or pull results via the Apify API. ### Why use it - **Fresh results** — filter by the past hour, 24 hours, week or month. - **Remote filter** — restrict results to remote-eligible postings in one click. - **Full descriptions** — optionally fetch the complete job description for each posting, ready for keyword analysis or LLM scoring. - **Clean output** — deduplicates cross-geography mirrors of the same opening (e.g. the same role posted under five country pages collapses to one record). ### What you get One dataset item per posting: | Field | Description | |---|---| | `title` | Job title | | `company` | Hiring company | | `location` | Location shown on the card | | `url` | Direct link to the posting | | `source` | Always `linkedin` | | `description` | Full plain-text description (optional) | ### Input | Field | Type | Default | Notes | |---|---|---|---| | `keyword` | string | — | Role, skill or title to search for | | `location` | string | — | City, region or country; empty = worldwide | | `remote` | boolean | `false` | Restrict to remote-eligible postings | | `timeFilter` | enum | `r86400` | `r3600` / `r86400` / `r604800` / `r2592000` (hour/day/week/month) | | `maxItems` | integer | `100` | Cap on results; `0` = all (up to ~200 per run) | | `includeDescription` | boolean | `true` | Fetch full description text per posting | #### Example ```json { "keyword": "software engineer typescript", "location": "Germany", "remote": false, "timeFilter": "r86400", "maxItems": 50, "includeDescription": true } ```` Returns up to 50 software-engineering postings in Germany published in the past 24 hours, each with the full job description. #### Remote worldwide example ```json { "keyword": "product manager", "remote": true, "timeFilter": "r604800", "maxItems": 200, "includeDescription": false } ``` Returns up to 200 remote product-manager roles from the past week, without fetching descriptions (faster). ### Use cases - Job seekers tracking fresh openings before they fill up. - Recruiters and staffing teams monitoring competitor hiring or talent supply. - Job aggregators and newsletter publishers pulling daily LinkedIn listings. - Labor-market researchers analyzing role demand by keyword and region. - LLM-powered job-matching pipelines that need full description text. # Actor input Schema ## `keyword` (type: `string`): Job title, skill or role to search for (e.g. "software engineer", "product manager react"). Leave empty to search all recent postings for the given location. ## `location` (type: `string`): City, region or country to filter by (e.g. "Spain", "London", "European Union"). Leave empty for worldwide results. ## `remote` (type: `boolean`): When enabled, restricts results to remote-eligible postings. ## `timeFilter` (type: `string`): Restrict to postings published within the chosen window. ## `maxItems` (type: `integer`): Maximum number of job postings to return. Set 0 for no limit (up to ~200 per run). ## `includeDescription` (type: `boolean`): Fetch and include the full plain-text job description for each posting. Disabling this makes runs faster and uses fewer requests. ## `cacheTtlSeconds` (type: `integer`): Cache the upstream fetch in the key-value store for this many seconds; re-runs within the window skip the network call. Set 0 to disable. ## Actor input object example ```json { "keyword": "frontend developer typescript", "location": "Germany", "remote": false, "timeFilter": "r86400", "maxItems": 100, "includeDescription": true, "cacheTtlSeconds": 1800 } ``` # 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("nomad-dev/linkedin-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("nomad-dev/linkedin-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 nomad-dev/linkedin-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nomad-dev/linkedin-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper", "description": "Collect recent job postings from LinkedIn's public job search by keyword and location. Returns structured records with title, company, location, URL and optional full description. No account or login required.", "version": "0.1", "x-build-id": "jjk2qeDBMKW0McDc2" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nomad-dev~linkedin-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nomad-dev-linkedin-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/nomad-dev~linkedin-scraper/runs": { "post": { "operationId": "runs-sync-nomad-dev-linkedin-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/nomad-dev~linkedin-scraper/run-sync": { "post": { "operationId": "run-sync-nomad-dev-linkedin-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": "Keyword", "type": "string", "description": "Job title, skill or role to search for (e.g. \"software engineer\", \"product manager react\"). Leave empty to search all recent postings for the given location." }, "location": { "title": "Location", "type": "string", "description": "City, region or country to filter by (e.g. \"Spain\", \"London\", \"European Union\"). Leave empty for worldwide results." }, "remote": { "title": "Remote only", "type": "boolean", "description": "When enabled, restricts results to remote-eligible postings.", "default": false }, "timeFilter": { "title": "Posted within", "enum": [ "r3600", "r86400", "r604800", "r2592000" ], "type": "string", "description": "Restrict to postings published within the chosen window.", "default": "r86400" }, "maxItems": { "title": "Max items", "minimum": 0, "type": "integer", "description": "Maximum number of job postings to return. Set 0 for no limit (up to ~200 per run).", "default": 100 }, "includeDescription": { "title": "Include full description", "type": "boolean", "description": "Fetch and include the full plain-text job description for each posting. Disabling this makes runs faster and uses fewer requests.", "default": true }, "cacheTtlSeconds": { "title": "Cache TTL (seconds)", "minimum": 0, "type": "integer", "description": "Cache the upstream fetch in the key-value store for this many seconds; re-runs within the window skip the network call. Set 0 to disable.", "default": 1800 } } }, "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 } } } } } } } } } } ```