LinkedIn has no public jobs API: 6 working alternatives compared

Is there a LinkedIn Jobs API for third parties?

No, and there never has been a self-serve one. LinkedIn's developer docs (Microsoft Learn, updated June 3, 2026) split access into three tiers. Open Permissions, the only ones any developer can enable, cover Sign In with LinkedIn and Share on LinkedIn. Marketing, Sales Navigator, and Talent programs all need explicit approval. Job data sits under Talent Solutions: Recruiter System Connect, Apply Connect, Apply with LinkedIn, and Premium Job Posting, each gated behind a partner application form. The Job Posting API overview page carries a notice that reads: 'We are currently not accepting new partnerships for LinkedIn's Job Posting API.' Even for approved partners, that API pushes jobs into LinkedIn on behalf of employers. It has no endpoint for searching or reading listings, so the phrase 'LinkedIn jobs API' describes a product that was never sold to the public. Every practical option reads the public jobs pages instead.

• Self-serve permissions as of June 2026: profile, email, and w_member_social. No jobs scope exists.
• Talent Solutions APIs require a partner application, an API agreement with data restrictions, and a LinkedIn relationship manager, per the Job Posting legal requirements section.
• The Job Posting API is write-only: it syncs Basic or Promoted jobs into LinkedIn and returns nothing you could call a search result.
• No Talent Solutions API has a published price; quotes arrive only after partnership approval.

Which LinkedIn jobs scraper should you use instead?

Six Apify actors cover most of the market, and every number below comes from each actor's live store page on August 29, 2026. curious_coder/linkedin-jobs-scraper is the incumbent: 142,306 users, 14,458 of them in the last 30 days, a 4.56 rating, from $1.00 per 1,000 results, and 99.7% of runs succeeding. cheap_scraper's 'Remove Duplicate Jobs' actor has 47,084 users and a 4.02 rating at $0.35 to $0.70 per 1,000 depending on your Apify plan, with a documented cap of 1,000 jobs per search. bebity charges $29.99 per month plus usage, rates 4.28 with 35,315 users, but only 257 people used it in the last 30 days, and Apify retires rental pricing on October 1, 2026. valig is the price floor at $0.28 per 1,000 with a 4.63 rating and 100% run success. apimaestro's 'No Cookies' actor costs $5.00 per 1,000 and rates 3.73. Datapika's job-board-scraper also bills $5 per 1,000 (2,471 users, 381 in the last 30 days, 5.0 from 3 reviews, 100% run success) and is the only row covering 8 boards with cross-board deduplication. Datapika loses on per-row price; it wins on rating, source coverage, and agent access.

• Cheapest per row: valig at $0.28 per 1,000, then cheap_scraper at $0.35 to $0.70.
• Largest install base: curious_coder at 142,306 users, roughly 3x cheap_scraper and 57x Datapika.
• Highest rating: Datapika at 5.0 (3 reviews), then valig at 4.63 and curious_coder at 4.56.
• Multi-board sweep, LinkedIn company-ID targeting, and an MCP endpoint: Datapika only.
• Explicit no-login, no-cookie operation stated on the listing: cheap_scraper, apimaestro, and Datapika.

What does it cost to scrape 1,000 or 10,000 LinkedIn jobs?

Pay-per-result actors make the arithmetic simple: multiply the row count by the per-row rate. Rental actors do not, because a flat monthly fee is cheap at volume and expensive at low volume. Using the August 29, 2026 store prices: valig at $0.00028 per job costs $0.28 for 1,000 jobs and $2.80 for 10,000. curious_coder at $0.001 per job costs $1.00 and $10.00. Datapika at $0.005 per job costs $5.00 and $50.00, so on a LinkedIn-only pull it is 5x curious_coder and about 18x valig. bebity's $29.99 rental works out to $29.99 per 1,000 if you only need 1,000 jobs a month, or $3.00 per 1,000 at 10,000 jobs, before Apify compute charges on top. The Datapika premium buys deduplication: a job posted on LinkedIn, Indeed, and Glassdoor is billed once as a single row tagged with all three sources, so a 10,000-row multi-board pull costs $50 rather than three separate actor bills. If you only want LinkedIn rows at volume, the same catalog has a $0.0005 per job LinkedIn-only option, which prices 10,000 jobs at $5.00.

• 1,000 jobs: valig $0.28, curious_coder $1.00, cheap_scraper $0.35 to $0.70, apimaestro $5.00, Datapika $5.00, bebity $29.99 plus usage.
• 10,000 jobs: valig $2.80, curious_coder $10.00, cheap_scraper $3.50 to $7.00, apimaestro $50.00, Datapika $50.00, bebity $29.99 plus usage.
• Break-even for bebity against curious_coder is about 30,000 jobs per month ($29.99 divided by $0.001), and that comparison ends when rental billing stops on October 1, 2026.
• Datapika's $5 covers up to 8 boards per row; the LinkedIn-only budget option in the same catalog is $0.0005 per job.

Can you scrape LinkedIn jobs without login or cookies, and what fields do you get?

Yes. LinkedIn serves a public version of job search to logged-out visitors, which is why curious_coder's README tells you to copy search URLs from an incognito window. cheap_scraper, apimaestro, and Datapika state on their listings that no credentials are needed; apimaestro's page frames it as not risking your account by sharing cookies. Cookie-based scrapers exist for the logged-in feed, but they expose your own profile to restriction, which is why 'No Cookies' and 'No Login' now appear in actor titles. The trade-off is scope. cheap_scraper documents a 1,000-result ceiling per search, Datapika's listing notes LinkedIn rate-limits to about 100 results per IP and recommends residential proxies for large runs, and curious_coder's page reports that LinkedIn's August 2026 AI-powered search honors only four URL filters: date posted, company, easy apply, and under 10 applicants. Datapika's schema is the widest of the group because it normalizes LinkedIn rows against 7 other boards.

• Core fields on every Datapika row: title, company, location, job URL, direct apply URL, remote flag, and job type.
• Salary: min, max, currency, and interval, with optional annual normalization for cross-board comparison.
• Company enrichment: size, revenue, rating, review count, industry, and logo.
• Full description in markdown or HTML when linkedinFetchDescription is on.
• Targeting: linkedinCompanyIds restricts a run to named employers; hoursOld filters recency but cannot be combined with easyApply on LinkedIn, per the store listing.
• curious_coder adds job-poster details; cheap_scraper adds a saveOnlyUniqueItems switch to avoid paying for duplicates within LinkedIn.

When to choose which LinkedIn jobs API alternative

Pick by the shape of the job, not by the headline price. A one-off LinkedIn keyword dump has a different cost curve from a weekly competitor watch across every board an employer posts on, and an AI agent that needs a tool endpoint has different requirements again. Volume matters too: below roughly 30,000 jobs a month every pay-per-result actor in the table undercuts bebity's $29.99 rental, and above that the rental only wins until Apify retires the model on October 1, 2026. Check run success before price, because a cheap actor that fails on the URLs you feed it costs engineering hours instead of cents: valig, apimaestro, and Datapika each report 100% run success, curious_coder and cheap_scraper 99.7%, and bebity 99.2%. All figures are as of August 29, 2026.

• Lowest cost, LinkedIn only: valig ($0.28 per 1,000, 4.63) or cheap_scraper ($0.35 to $0.70, built-in dedup, 1,000-result cap per search).
• Safest default for a large team: curious_coder ($1.00 per 1,000, 142,306 users, 99.7% run success), accepting that LinkedIn's new search limits URL filters.
• Tracking named employers across boards: Datapika ($5 per 1,000, LinkedIn company-ID targeting, one deduplicated row per job across 8 boards, 5.0 rating).
• AI agents and MCP clients: Datapika, reachable through the Apify MCP server with pay-per-result billing and no API key of its own.
• High-volume LinkedIn-only feeds: the $0.0005 per job LinkedIn-only option in the Datapika catalog.
• Avoid starting a new pipeline on bebity's $29.99 rental; Apify retires rental pricing on October 1, 2026 and migrates remaining rental actors to pay-per-usage billing.

Questions, answered

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