LinkedIn Jobs Database API — Advanced Search + Decision Makers

What does LinkedIn Jobs Database API do?

LinkedIn Jobs Database API is a search over our database of 50M+ LinkedIn job postings from the last 180 days, with the filters a database can apply exactly and two things a plain job feed cannot give you: a free breakdown of the market before you buy a single row, and the people behind each posting: the recruiter named on it, the employer's hiring pace, and the employer's decision makers.

One Actor, three jobs:

1. Search jobs with database-grade filters. Title and description search with boolean operators and exclusions, locations with exclusions, exact employers and employer size, industry, seniority, employment type, salary as a number in a currency, applicant count, years of experience required, recruiter-only, posting window, and expired postings as a filter rather than a second product. Up to 10,000 jobs per run, newest first, each job once.
2. Measure the market, free. previewOnly returns how many postings match and their split by country, seniority, employment type, industry, top employers, titles and cities. No charge.
3. Reach the people who hire. Every row carries the recruiter card when the posting names one. employerHiring adds the employer's open roles and posting pace. decisionMakers adds the founders, C-level, VPs and directors of each hiring employer as rows of their own, with the email on record when the contact tier is on.

$0.80 per 1,000 jobs, company card and recruiter card included. $3.20 per 1,000 decision makers. Counts, misses and refused inputs are free. No cookies, no login, no API key of yours.

At a glance

What you get	One row per job: title, description (text or HTML), location, posted date, seniority, employment type, salary, applicants, required experience, benefits, the company card (website, industry, headcount, country, funding), the recruiter card
Search by	Title and description (boolean, exclusions), location (country, US state, city; country exclusions), exact employers and employer name, employer size, industry (with exclusions), seniority, employment type, salary floor, applicant ceiling, years of experience, recruiter-only, posting window or date, status (active, expired, any)
Price	$0.80 per 1,000 jobs; company and recruiter cards included; counts and misses free
Speed	1,000 jobs in about 30 seconds (measured 26 October 2026)
Scale	Up to 10,000 jobs per run; free Apify plan up to 100
People	Recruiter card (free), the employer's hiring pace (free), the recruiter's full profile, the employer's decision makers with emails on record
Feeds	New postings with timeRange: "24h" on a schedule; closed postings with status: "expired" and expiredAfter
Runs from	Apify Console, REST API, schedules and webhooks, n8n, Make, Zapier, and MCP for AI agents

How does it compare with the LinkedIn jobs database API on this Store?

Read from that Actor's Store page and README on 26 October 2026.

	LinkedIn Jobs Database API (this Actor)	The jobs database API on this Store
Price per 1,000 jobs	$0.80 on every plan	$5.00 on the Free and Starter plans, $1.50 on Business
Recruiter on the row	Free card; the recruiterOnly filter is free	An extra per-row charge that triples the price of a row with a recruiter
Expired postings	A filter in the same run (status, expiredAfter)	A separate Actor at $20 a month
Count before you pay	Free, with the breakdown by country, seniority, type, industry, employer, title and city	None
Jobs per run	10,000	5,000
Locations	Country, US state or city by name or code (UK, gb, London)	Exact City, State, Country format, English names, no abbreviations
Seniority filter	Every country; half to two thirds of developer postings name a level (Entry, Mid-Senior, Director …), the rest read Not Applicable	English-speaking countries only
The employer's hiring pace on the row	Free	No
Decision makers of the employer	$3.20 per 1,000 people	No
Remote / hybrid, Easy Apply, visa sponsorship, AI-derived fields	Not in this database: refused, never faked	On technology roles
Freshness	Reloaded after each data update; every row carries dataAsOf	Indexed continuously, about an hour behind

The last two rows are the honest part. If you need a remote flag or hourly freshness, that API is the better tool today. If you need exact filters, a count before you pay, the recruiter for free and the people to contact, this one is.

Who uses it, and how?

If you are	You can	Start with
A job board or aggregator	Fill and refresh a board: new postings every day, closed ones removed by their jobId	timeRange: "24h" on a daily schedule; a second schedule with status: "expired", expiredAfter
A recruiter or sourcing team	Find the roles your candidates fit, with the recruiter to write to, and skip agencies	titleSearch, locationSearch, recruiterOnly: true, removeAgency: true
A B2B sales team	Spot companies hiring for the problem you solve and get the decision makers in the same run	titleSearch, organizationEmployeesGte, organizationEmployeesLte, removeAgency: true, decisionMakers: true
A market or HR analyst	Size demand for a skill or a role by country and city, benchmark published salaries, follow a technology through the descriptions	previewOnly: true first; then descriptionSearch with titleSearch and hasSalary: true
A competitive-intelligence team	Watch competitors' hiring: roles, levels, locations, pace	organizationSlugFilter, timeRange: "30d", employerHiring: true
An AI agent builder	Give an agent live job data through MCP, with a free count before any paid call	The AI agents section below

What data do you get for each job?

Field	Example	Filled
jobId, url	4012345678, https://www.linkedin.com/jobs/view/4012345678/	always
title	Senior Software Engineer, Payments	always
postedAt, validUntil, isOpen, closedAt	2026-10-15T09:30:00Z, true	always; validUntil when stated, closedAt on expired postings
companyName, companyDomain, companyIndustry, companyEmployeeCount, companyCountryCode, companyUrl	Example Corp, example.com, Software Development, 1240, US	the card is on 99% of postings
company	the full card: website, industry, headcount, HQ, founded, funding, description	same
locationText, location	Austin, TX; { countryCode, region, locality, postalCode, lat, lon }	always; coordinates on 57%
seniorityLevel, employmentTypeName	Mid-Senior level, Full-time	99%; half to two thirds of developer postings name a level (Entry, Mid-Senior, Director …), the rest read Not Applicable
industries	[{ id: 4, name: "Software Development" }]	99%
salaryText, salary	$150K/yr - $190K/yr; { min, max, currency, period, annualMin, annualMax }	13% overall; 50% in the Netherlands, 41% in China
applicants, applicantRange	48, 25-50 applicants	the count on 10%, the bucket on every posting
requiredExperienceMonths, education, benefits	60, Bachelor degree, ["Medical insurance"]	experience on 22%
description, descriptionHtml	the posting text, plain and as HTML	when descriptionType asks for it
recruiterName, recruiterHeadline, recruiterUrl, recruiter	Jane Doe, Technical Recruiter at Example Corp	on the 11% of postings that name one (28% in India, 17% in the UK, 7% in the US)
recruiterProfile	the recruiter's full career profile	with recruiter: "profile", where the profile is on record
employerOpenJobs, employerJobs7d, employerJobs30d, employerJobs90d, employerLastPostedAt, employerTopTitles30d, employerHiring	42, 6, 19, 41, 2026-10-21T08:00:00Z, ["Software Engineer", "Account Executive"]	with employerHiring: true, where the employer has a signal on record
_type, _status, _input	job, found, the filters and dataAsOf	always

Unknown facts are left out, never shipped as empty strings. Every row's _input.dataAsOf is the date of the newest posting in the database at the time of the run.

How to search LinkedIn jobs through the API (3 steps)

1. Enter title search terms and a location (a country by name or code, a US state, a city), or employer slugs.
2. Narrow with description search, exclusions, employer size, industry, seniority, employment type, salary, applicants, experience and the time range. Set Max jobs, your spend cap. Press Start. To size the search first, tick Preview only: the count and the breakdown are free.
3. Export the dataset as JSON, CSV or Excel, or read it through the API. Schedule it with timeRange: "24h" for a daily feed, and with status: "expired" for the expiry feed.

A search needs a country or an employer slug: a title alone, a city alone or an employer name alone is not a search here.

How do I search job descriptions for a technology?

Put the role in titleSearch and the technology in descriptionSearch: data engineer in the title, kubernetes in the description, Germany, last 30 days. The texts are read for the postings the other filters leave, so a description search needs a narrow cut: an employer in organizationSlugFilter, or a country with a time range of at most 30 days. A wider cut is refused before anything is charged, with the number of postings it would have to read.

How do I build a daily feed of new and closed jobs?

Two schedules of the same Actor. The first runs with timeRange: "24h" (or datePostedAfter set to your last run) and gives you the new postings; upsert them by jobId. The second runs with status: "expired" and expiredAfter set to yesterday and gives you the postings that closed; remove them by jobId. Each closed posting carries isOpen: false and closedAt.

How much does the job search API cost?

$0.80 per 1,000 jobs delivered ($0.0008 per job), plus the Actor start fee of $0.0002 per run.

Row	Price
Job delivered (_status: found, _type: job)	$0.0008
Company card and recruiter card on the row; the recruiterOnly filter	$0, included
The employer's hiring pace on the row (employerHiring: true)	$0, included
Recruiter's full profile (recruiter: "profile"), per job that carries one	$0.0032
Decision maker of the employer (decisionMakers: true), per person	$0.0032
Preview and breakdown rows (previewOnly)	$0
Search that matches nothing, refused input, posting skipped by the employer-size bound	$0

limit is your spend cap: at the default of 100 a run costs at most $0.08 for the jobs. Prices are the same on every Apify plan.

Input

The form has five sections: Search, Employers, More filters, People behind the job and Output. An agent or an API call sends the same field names as JSON:

{
  "titleSearch": ["software engineer", "backend engineer"],
  "titleExclusionSearch": ["intern", "staff engineer"],
  "locationSearch": ["United States"],
  "limit": 500,
  "timeRange": "7d",
  "descriptionSearch": ["kubernetes"],
  "organizationSlugExclusionFilter": ["acme-staffing"],
  "organizationEmployeesGte": 51,
  "organizationEmployeesLte": 5000,
  "removeAgency": true,
  "industryFilter": ["Software Development"],
  "seniorityFilter": ["Mid-Senior level"],
  "employmentTypeFilter": ["FULL_TIME"],
  "status": "active",
  "recruiter": "card",
  "employerHiring": true,
  "descriptionType": "text"
}

Search

• titleSearch, titleExclusionSearch: words or phrases the title must (not) contain; whole words, any case; a line may use AND, OR, NOT, "exact phrase", parentheses. Up to 10 each. Prefix matching (soft:*) is not available and is refused.
• locationSearch: countries by name or code (United States, Germany, gb, UK), US states (California), cities (Berlin, Austin, Texas). Any of them. locationExclusionSearch takes whole countries only.
• limit: jobs per run (default 100, 0 = up to 10,000). Free Apify plan: up to 100.
• previewOnly: the count and breakdown instead of the rows, free. compact: short rows for AI agents.
• timeRange: 24h, 7d (default), 30d, 90d, 6m (everything, 180 days).
• descriptionSearch, descriptionExclusionSearch: the same over the posting text, for a narrow cut (see the FAQ). Up to 10 each.

Employers

• organizationSlugFilter, organizationSlugExclusionFilter: exact employers: the page slug (tesla-motors), a page URL, a website domain or a numeric id. Up to 100 each. An employer list alone is a complete search.
• organizationSearch: employer names, matched as part of the recorded name (Google matches Google Cloud); several companies share a name, so use organizationSlugFilter for an exact employer. organizationExclusionSearch is not available; exclude by slug.
• organizationEmployeesGte, organizationEmployeesLte, organizationSizeFilter: the employer's headcount on record; postings at employers outside the bounds, or with no headcount on record, are skipped free.
• removeAgency: drops postings by staffing firms and job-board aggregators (by the posting's industry, and by the employer's own card: its industry and what its description says it does), and by employers with far more postings than employees (at least 200 open, or 100 posted in the last 30 days, and more than two per employee).

More filters

• seniorityFilter: Internship, Entry level, Associate, Mid-Senior level, Director, Executive, Not Applicable.
• employmentTypeFilter: FULL_TIME, PART_TIME, CONTRACTOR, TEMPORARY, INTERN, VOLUNTEER, OTHER (aiEmploymentTypeFilter is accepted as the same field; PER_DIEM is not in this data).
• industryFilter, industryExclusionFilter: industry names (Software Development) or numeric ids; an industry covers its sub-industries. Up to 30 each.
• hasSalary, salaryMin, salaryCurrency: only postings that state a salary; at least this yearly amount, in the given currency (default USD).
• maxApplicants: 25 … 200: the applicant bucket (25 wide) the posting is in or below.
• aiExperienceLevelFilter: 0-2, 2-5, 5-10, 10+ years of required experience, as the posting states it; about one posting in five states one, the others never match. Adjacent ranges are joined.
• recruiterOnly: only postings that name the recruiter or hiring manager. Free.
• datePostedAfter: a date instead of the window; with both, the later bound wins.
• status: active (default), expired, any; expiredAfter narrows expired postings to those closed on or after a date.

People behind the job

• recruiter: card (default, free), profile ($3.20 per 1,000 jobs that carry one) or none.
• employerHiring: the employer's hiring signal on each row, free: employerOpenJobs, employerJobs7d, employerJobs30d, employerJobs90d, employerLastPostedAt, employerTopTitles30d.
• decisionMakers, decisionMakerRoles, decisionMakersPerCompany, decisionMakerTitleKeywords: the leadership add-on, see below.

Output

• descriptionType: text (default), html, both, none. Same price.

Output

One row per job. The flat columns lead, then the job as recorded. Values below are made up:

{
  "_status": "found",
  "_type": "job",
  "_input": { "filters": { "title": "(software engineer) NOT intern", "countries": ["us"], "posted_after": "2026-10-19T12:00:00Z" }, "dataAsOf": "2026-10-21" },
  "jobId": 4012345678,
  "title": "Senior Software Engineer, Payments",
  "url": "https://www.linkedin.com/jobs/view/4012345678/",
  "postedAt": "2026-10-15T09:30:00Z",
  "companyName": "Example Corp",
  "companyDomain": "example.com",
  "companyIndustry": "Software Development",
  "companyEmployeeCount": 1240,
  "companyCountryCode": "US",
  "locationText": "Austin, TX",
  "countryCode": "US",
  "seniorityLevel": "Mid-Senior level",
  "employmentTypeName": "Full-time",
  "salaryText": "$150K/yr - $190K/yr",
  "applicantRange": "25-50 applicants",
  "recruiterName": "Jane Doe",
  "recruiterUrl": "https://www.linkedin.com/in/jane-doe-example",
  "employerOpenJobs": 42,
  "employerJobs7d": 6,
  "employerJobs30d": 19,
  "employerJobs90d": 41,
  "employerLastPostedAt": "2026-10-21T08:00:00Z",
  "employerTopTitles30d": ["Software Engineer", "Account Executive"],
  "isOpen": true,
  "validUntil": "2026-11-14T09:30:00Z",
  "location": { "text": "Austin, TX", "countryCode": "US", "region": "TX", "locality": "Austin" },
  "seniority": { "id": 16, "name": "Mid-Senior level" },
  "employmentType": { "id": 1, "name": "Full-time" },
  "industries": [{ "id": 4, "name": "Software Development" }],
  "salary": { "min": 150000, "max": 190000, "currency": "USD", "period": "year", "text": "$150K/yr - $190K/yr" },
  "requiredExperienceMonths": 60,
  "description": "About the role…",
  "company": { "id": 123456, "name": "Example Corp", "domain": "example.com", "employeeCount": 1240, "industry": "Software Development", "countryCode": "US", "funding": { "hasFunding": true, "lastRoundType": "series_c" }, "hq": { "locality": "Austin, TX", "region": "TX" } },
  "recruiter": { "kind": "person", "slug": "jane-doe-example", "url": "https://www.linkedin.com/in/jane-doe-example", "fullName": "Jane Doe", "headline": "Technical Recruiter at Example Corp" },
  "employerHiring": { "openJobs": 42, "jobs7d": 6, "jobs30d": 19, "jobs90d": 41, "lastPostedAt": "2026-10-21T08:00:00Z", "seniorities30d": [{ "id": 16, "name": "Mid-Senior level", "count": 11 }], "countries30d": ["us"], "topTitles30d": ["Software Engineer", "Account Executive"], "asOf": "2026-10-22T00:00:00Z" }
}

The employer… columns are there when employerHiring is on. An expired posting carries isOpen: false and closedAt. Free rows say why they are not a result: no_results, invalid (an employer entry that could not be read), input_problem (a refused input, with the field named), no_decision_makers, error (nothing charged).

The Output tab has five views: Overview, Company & recruiter, Employer hiring, Decision makers and Preview & breakdown.

Decision makers: from a job to the people who hire

Turn on decisionMakers and every employer in the result is followed by its decision makers, each as a row of its own (_type: decision_maker): founders and owners, C-level, VPs and directors, ranked founder + CEO first, assistants and "Office of the CEO" staff removed, each person once per run. Each row carries fullName, jobTitle, seniority, headline, linkedinUrl, location, forJobId and forJobTitle; the email that reaches the person today rides the row when one is on record and the contact tier is on.

• decisionMakerRoles: founder, cxo, vp, director; default all four.
• decisionMakersPerCompany: people per employer, in rank order (default 3, maximum 25).
• decisionMakerTitleKeywords: keep only titles containing any of these words (sales, engineering, talent). C-level acronyms (cto, coo, cfo …) match as whole words, so cto finds "Co-Founder & CTO" and not "Director".

$3.20 per 1,000 people delivered; an employer with nobody at the chosen roles is a free row. For the same list without the jobs, use Companies Hiring Now.

Use LinkedIn Jobs Database API with AI agents and MCP

This Actor works as a tool for AI agents. Add it to Claude, ChatGPT, Cursor or any other MCP client through the Apify MCP server:

https://mcp.apify.com?tools=b2bsearch/linkedin-job-search-api

The same Actor is a tool in LangChain, CrewAI and the OpenAI Agents SDK, and a step in n8n, Make and Zapier through the Apify integrations.

What an agent should know before calling it

• When to pick it. The user wants LinkedIn job postings with precise filters (keywords in the description, exclusions, employer size, industry, seniority, salary, applicants, experience), a count of the market, expired postings, or the people behind the postings (recruiter, hiring pace, decision makers). For a plain title-and-location scrape in the best-known scraper's field names, Advanced LinkedIn Jobs Scraper does the same rows. For the list of companies hiring, Companies Hiring Now.
• Minimal input. titleSearch (array) plus locationSearch (array with at least one country), or organizationSlugFilter (array). limit is the number of rows to buy; the default is 100.
• Count first. Send previewOnly: true to get the number of matches and their breakdown for free, then decide how many rows to buy.
• Cost. $0.0008 per found job row, $0.0032 per decision-maker row; rows with any other _status are free. Cap a call with maxTotalChargeUsd in the run options.
• Read the rows. _status is found for a job; _type is job, decision_maker or preview. A row that is not a result says why in _status and _error. The useful columns are flat: title, companyName, companyDomain, companyEmployeeCount, locationText, postedAt, seniorityLevel, employmentTypeName, salaryText, applicantRange, recruiterName, recruiterUrl, employerOpenJobs, url.
• Small rows. compact: true keeps every plain column and cuts the description to 300 characters. descriptionType: "none" drops it.
• Refusals are exact. A field this database cannot answer (remote, Easy Apply, visa, language) stops the run before any charge and names the field. Do not retry with the same field.
• Fast. A small request finishes in seconds, inside one tool call.

Input an agent can send as is:

{
  "titleSearch": ["software engineer"],
  "locationSearch": ["United States"],
  "timeRange": "7d",
  "limit": 25,
  "compact": true
}

Example prompts

Use b2bsearch/linkedin-job-search-api with previewOnly true: how many "product manager" jobs were posted in the United Kingdom in the last 30 days, and how do they split by seniority, industry and city?

Use b2bsearch/linkedin-job-search-api: titleSearch ["data engineer"], descriptionSearch ["kubernetes", "airflow"], locationSearch ["Germany"], timeRange 30d, removeAgency true, hasSalary true, 50 rows. Summarise the salary ranges and list the employers.

Use b2bsearch/linkedin-job-search-api: titleSearch ["head of sales", "VP sales"], locationSearch ["United States"], organizationEmployeesGte 51, organizationEmployeesLte 1000, timeRange 7d, decisionMakers true, decisionMakerRoles ["founder", "cxo"], 40 rows. For each company give me the role, the posting date and the two people to contact.

Use b2bsearch/linkedin-job-search-api: organizationSlugFilter ["stripe.com", "shopify.com"], timeRange 6m, status expired, expiredAfter 2026-10-01. Which roles did they close this month?

Migrating from another LinkedIn jobs API

Your saved input runs as it is: the field names and values are the same.

Their field	Here
titleSearch, titleExclusionSearch, descriptionSearch, descriptionExclusionSearch, locationSearch, locationExclusionSearch, organizationSearch, organizationSlugFilter, organizationSlugExclusionFilter, organizationEmployeesGte, organizationEmployeesLte, organizationSizeFilter, industryFilter, industryExclusionFilter, seniorityFilter, aiEmploymentTypeFilter, hasSalary, removeAgency, recruiterOnly, timeRange, datePostedAfter, descriptionType, limit	same names, same values
aiExperienceLevelFilter	same values, applied to the experience the posting states (not an AI estimate)
timeRange: "1h"	use 24h: the database is reloaded after each data update, not every hour
:* prefix matching	not available: words match whole
excludeATSDuplicate, populateAiRemoteLocation*, includeAi	accepted and ignored: there are no career-site duplicates and no AI fields here
organizationExclusionSearch	not available: exclude by organizationSlugExclusionFilter
aiWorkArrangementFilter, remote, aiVisaSponsorshipFilter, directApply, noDirectApply, aiTaxonomies*, aiLanguageFilter, hasNoLocation	not in this database: a run that sets one stops before anything is charged and names the field
the Expired Jobs API	status: "expired" with expiredAfter, in the same run
recruiterOnly surcharge	none: the filter and the recruiter card are free

The refusals are deliberate. A remote-only run that silently came back with office jobs would be a wrong answer sold as a right one.

FAQ

How fresh is the data, and how do I run a sync?

The database holds the last 180 days of postings and is reloaded after each data update, not every hour. Every row says what the data runs to: _input.dataAsOf is the date of the newest posting at the time of your run. For new postings, schedule the Actor with timeRange: "24h" or datePostedAfter set to your last run; for closed ones, a second schedule with status: "expired" and expiredAfter.

Is this a scraper or an API?

An API over a database we fill and refresh ourselves. Nothing runs against LinkedIn when you press Start, which is why a search takes seconds, needs no cookies and charges nothing for a miss. The rows are what a scraper would give you, plus what a scraper cannot: the count before you pay, the employer's hiring pace and its decision makers.

Why does the description search need a narrow cut?

The posting texts are read one by one for the postings the other filters leave, and the service reads at most 500 of them per request. "Kubernetes anywhere in Germany this month" is a quarter of a million texts and is refused before anything is charged, with that number; "kubernetes" in the descriptions of data engineer postings in Germany this week, or of one employer's open roles, is a few hundred and runs in seconds. Put the role in titleSearch and the technology in descriptionSearch.

What does the employer's hiring pace tell me?

employerHiring: true puts the employer's signal on each job row: how many postings it has open now, how many it posted in the last 7, 30 and 90 days, when it last posted and which titles it posts most. An employer with 40 open roles and 20 posted this month is scaling; one with a single posting is filling a seat. It is free and comes from the same database.

Can I filter remote jobs, Easy Apply, visa sponsorship or the posting's language?

Not yet: none of these is recorded in the database, so the fields are refused rather than faked. A titleSearch for remote finds the postings that say so in the title: about 1 in 100 US postings of the last month (27,000 of 2.5 million on 26 October 2026), a sample rather than the remote market.

Are there duplicate jobs?

Each posting is one row with its own jobId, delivered and charged once per run even when it matches several of your search terms. An employer that posts the same role in several cities has several postings, as on the source; deduplicate on title + companyId for one row per role.

How is the employer-size filter applied?

On the employer's headcount on record. A posting at an employer outside the bounds, or with no headcount on record, is skipped and not charged; the run reads on until your limit is met or 2,000 postings have been skipped. The free preview counts every posting the other filters match: the bound is applied to the rows, so a bounded run returns fewer rows than the preview's count, and the preview says so.

Am I charged when nothing is found?

No. Empty searches, unusable employer entries, skipped postings and refused inputs are free rows with a _status and an explanation. Only found rows are charged.

Does it need cookies, a login or an API key?

No. The Actor does not sign in to any website and asks for no credentials.

Related Actors: which one should you use?

Need	Actor
Database-style job search: description keywords, exclusions, employer size, expired postings, decision makers	LinkedIn Jobs Database API (this Actor)
Jobs by title, location and company, in the input names of the best-known scraper	Advanced LinkedIn Jobs Scraper
The companies hiring for a role, with their hiring pace and decision makers	Companies Hiring Now
Company domain → decision makers	Decision Maker Email Finder by Domain
Company domain → current employees	Company Employees
LinkedIn URL → full profile	Profile Lookup
Filters → list of people	People Database Search
Filters → leads with an email	B2B Leads Finder
Filters → list of companies	Company Database Search

Free Apify plan

A run started from a free Apify plan delivers the first 100 results and stops; the run's status line says so. Any paid Apify plan lifts the cap. The rows are the same rows a paid run returns.

Feedback and reviews

How did it go? A rating in the Reviews tab of this Actor tells the next buyer what to expect; we read every word, good or bad. Got a wrong or stale row? Open the Issues tab with the run ID. Issues are public, so leave out emails, phones and names; the run ID is enough for us to find the row. We check every report, fix what is ours to fix and answer in the thread.

Disclaimer and permitted use

Independent product. This Actor is an independent tool. It is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a trademark of its owner. It is named here only to describe the kind of public job postings and profile links this Actor returns.

No platform access. This Actor does not log in to, crawl or collect pages from LinkedIn or any other service. Every answer comes from our own database of job postings and business-contact records. It never returns passwords, messages, or content from non-public accounts.

Permitted use. Business purposes only: job market research, recruiting, sales prospecting, CRM enrichment and building job feeds. You may not use this Actor or its output to:

• stalk, harass, threaten, dox or publicly expose any person;
• decide on anyone's eligibility for credit, employment, housing or insurance. This Actor is not a consumer reporting agency and its output is not a consumer report under the U.S. Fair Credit Reporting Act;
• send unsolicited bulk messages, or place autodialed or prerecorded calls or texts without the consent the law requires;
• profile people by health, religion, political opinion, sexual orientation, ethnicity or union membership;
• build or resell a contact database from the results.

Your responsibilities. You decide what to search for and what to do with the result. You are responsible for having a lawful basis for that use and for complying with the laws that apply to you, including GDPR and UK GDPR, ePrivacy and PECR, CCPA/CPRA, CAN-SPAM, and the TCPA and Do Not Call rules. Honor every opt-out you receive.

Removal requests. To have a person's data removed, open an issue on this Actor with only the profile link. Nothing else is needed, and the record is removed from every listing.

Accuracy. Records can be incomplete or out of date. Output is provided as is. Check before you rely on it.