# Get LinkedIn jobs, company pages and posts in one run

**Use case:** 

Keywords, company slugs and post links together; jobs, company rows with exact counts and posts come back in one flat dataset with a type on every row.

## Input

```json
{
  "keywords": [
    "data engineer"
  ],
  "locations": [
    "United States"
  ],
  "datePosted": "week",
  "companies": [
    "microsoft",
    "nvidia"
  ],
  "companyScope": [
    "details",
    "posts"
  ],
  "includeComments": false,
  "easyApply": false,
  "under10Applicants": false,
  "maxItemsPerQuery": 25,
  "includeJobDetails": true,
  "includeCompany": false,
  "monitorChangesOnly": false,
  "maxItems": 80,
  "useProxy": false
}
```

## Output

```json
{
  "type": {
    "label": "Type",
    "format": "text"
  },
  "id": {
    "label": "Job id",
    "format": "text"
  },
  "title": {
    "label": "Title",
    "format": "text"
  },
  "companyName": {
    "label": "Company",
    "format": "text"
  },
  "location": {
    "label": "Location",
    "format": "text"
  },
  "postedAt": {
    "label": "Posted",
    "format": "date"
  },
  "seniorityLevel": {
    "label": "Seniority",
    "format": "text"
  },
  "employmentType": {
    "label": "Type",
    "format": "text"
  },
  "workplaceType": {
    "label": "Workplace",
    "format": "text"
  },
  "salaryText": {
    "label": "Salary",
    "format": "text"
  },
  "applicantsText": {
    "label": "Applicants",
    "format": "text"
  },
  "url": {
    "label": "URL",
    "format": "link"
  },
  "searchQuery": {
    "label": "From search",
    "format": "text"
  }
}
```

## About this Actor

This example demonstrates how to use [LinkedIn Scraper API - Jobs, Companies, Posts, Articles](https://apify.com/vonsensey/linkedin-scraper-api.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/vonsensey/linkedin-scraper-api.md) to learn more, explore other use cases, and run it yourself.


## 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.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/vonsensey/linkedin-scraper-api.md

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).