LinkedIn data, no LinkedIn account needed
Jobs and companies from LinkedIn's public pages, by API, MCP or files. You never connect an account, and you pay a flat price per request, not per row: a fraction of what Coresignal and TheirStack charge.
Two datasets
Both are collected from LinkedIn's logged-out pages around the clock, so nothing runs on a LinkedIn account.
Jobs
8.4 million
job posts since April 2026, about 45,000 more a day
Title, company, location, seniority, employment type, job functions, industries, salary, applicant count and the full description.
Companies
560,000+
companies that posted a job
Industry, size, exact staff count, followers, founding year, headquarters, office locations, specialties, website, and the jobs each company posted in the last 30 days. Filled from each company's public LinkedIn page and refreshed every 30 days while it keeps posting.
Three ways to get it
Credits pay for the dashboard, API and MCP: free credits every month, no subscription, and unused credits roll over for 12 months. For files, write to us.
- Dashboard
- Search and filter jobs and companies, then save the ones that matter as leads.
- API and MCP
- Plain HTTPS and JSON, or the hosted MCP server for Claude, Cursor and other AI apps. A jobs search returns up to 50 jobs for 1 credit.
- Files
- Every UTC day of jobs is one Parquet or CSV file with a manifest of row counts and checksums. A day's file is final two days later. Get the full history, each new day as it lands, or both: write to us.
API and MCP, per request
Search jobs
1credit
Get one job with its description
1credit
Get a company
1credit
Dataset files
Every job since April 2026, 8.4 million posts, as Parquet or CSV files, plus a daily feed if you need one. Write to us and we’ll send the details.
Compared with Coresignal and TheirStack
They charge per row; we charge per request. Both have far more history and sources than we do, and the table says so.
| Compared on | LinkFetch | Coresignal | TheirStack |
|---|---|---|---|
| 1,000 jobs through the API | 20 credits ($0.20): 50 jobs per request | 1,000 credits ($19.60 on the $49 plan) | 1,000 credits ($32.67 on the $49 plan) |
| One company record | 1 credit ($0.01) | 10–20 credits ($0.20–$0.39 on the $49 plan) | 3 credits ($0.10 on the $49 plan) |
| Bulk jobs dataset | Full history and daily feed on request; free 1,000-job sample | From $1,000, yearly contract | Contact sales |
| To get started | Free credits every month, no subscription | 7-day trial, then from $49 a month | Free monthly credits, then from $49 a month |
| Job posts | 8.4 million, LinkedIn only, since April 2026 | 482M+ | 225M+, many job boards, since 2021 |
| Companies | 560,000+ that posted jobs | 70M+ | 13M+ with technographics |
| Employee profiles | Through your own connected account only, never sold | 907M+ for sale |
Competitor prices from their public pricing pages on October 7, 2026, at their entry plans; their larger plans cost less per row. LinkFetch dollar figures assume $0.01 per credit. Sources: Coresignal pricing, TheirStack pricing, TheirStack credits, TheirStack datasets.
What a job row looks like
Real rows from the free sample, which uses the same columns as the files.
| title | company_name | location | seniority | salary | applicant_count |
|---|---|---|---|---|---|
| Assistant Financial Accountant | Quinn and Associates | Dublin, Ireland | associate | 45,000–55,000 EUR / year | 38 |
| Major Gift Officer, Athletics Advancement | Merrimack College | North Andover, MA | not_applicable | 85,000–100,000 USD / year | 27 |
| Software Test Engineer Freshers | Unique Infotech | India | entry | 420,000–460,000 INR / year | 58 |
| Fox Fire Center Analyst | California Department of Forestry and Fire Protection (CAL FIRE) | San Diego County, CA | not_applicable | 3,861–6,276 USD / month | 41 |
Job columns
The API and every file share these columns. Coverage notes show where LinkedIn often leaves a field out.
- job_id
- LinkedIn's job id; linkedin.com/jobs/view/<job_id> opens the post.
- title, title_id
- Title as posted, plus LinkedIn's standardized title id, which groups “Sr. SWE” with “Software Engineer III”.
- company_id, company_name, company_slug
- The hiring company. company_id joins to the company data.
- company_id on about 98%
- location, country_code, geo_id
- Location as LinkedIn shows it, plus the country and LinkedIn geo of the search that found the job.
- seniority, employment_type
- Normalized values such as mid_senior or full_time.
- job_functions, industries, industry_ids
- Functions as a list; industries as LinkedIn wrote them, with ids for filtering.
- posted_at, posted_at_exact
- When the job was posted. Exact to the second when LinkedIn reveals it, otherwise the day.
- exact on about 83%
- description, description_html
- The full job description as text and HTML, with contact details redacted.
- salary_raw, salary_min, salary_max, salary_currency, salary_period
- Pay as written and parsed into numbers, currency and period.
- on about 10%
- applicant_count, applicant_count_capped, applicant_count_early
- Applicants LinkedIn showed, whether it was a ceiling such as “over 200”, and “be among the first 25”.
- on about 8%
- first_seen_at, last_seen_at, fetched_at, closed_at
- When we first and last saw the job in search, last read its page, and found it closed.
Query the files where they land
Parquet opens in DuckDB, Polars, pandas, Spark, BigQuery or Snowflake without an import step.
-- Which companies started hiring engineers this month? (DuckDB)
SELECT company_name, country_code, count(*) AS openings
FROM read_parquet('linkfetch-jobs/day=*/jobs.parquet', hive_partitioning = true)
WHERE first_seen_at > now() - INTERVAL 30 DAY
AND list_contains(job_functions, 'Engineering')
GROUP BY ALL
HAVING count(*) >= 5
ORDER BY openings DESC;What it is not
- Not every job on the internet
- LinkedIn only, from LinkedIn's public job pages, across the regions we scan. Searches that hit LinkedIn's 1,000-result cap are split into smaller areas, but some jobs are still missed.
- Not years of history
- Collection started in April 2026, so the history is months deep and grows every day.
- Not complete on every field
- LinkedIn shows salary on about 10% of posts and applicant counts on about 8%; we carry exactly what LinkedIn showed.
- Not personal data
- No profiles are sold. Contact emails, phone numbers and profile links inside job descriptions are redacted. People data only comes through a LinkedIn account you connect, and stays private to you.
- Not affiliated with LinkedIn
- LinkFetch is an independent product.
Need something the data doesn’t cover? Write to info@linkfetch.io.