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MCPToolsSearch Job Openings

Search LinkedIn Job Openings

The advanced job search. Same market as linkedin_job_listings, but with company, quality and resume-matching filters on top.

Tool
search_linkedin_job_openings
Cost
0.3 credits
Category
Jobs
Required input
keywordlocations
Returns
LinkedIn job openings

What it does

  • Searches LinkedIn job openings across all companies, with a large filter set.
  • No single parameter is required, but you must pass at least keyword or locations — an unfiltered call has nothing to search on.
  • keyword and locations are arrays, so one call can cover several titles or several cities.
  • Filters go beyond the job itself: company size, founded date, follower count, whether the poster is a recruiting agency.
  • resume_keywords scores how well each opening matches a resume — the only job tool that does this.
  • Returns up to 100 openings per call. Default is 10.

There are four job tools. All four cost 0.3 credits, so pick by scope and input:

ToolScopeCost
linkedin_job_listingsAll companies, plain keyword search0.3 credits
search_linkedin_job_openingsAll companies, advanced filters and resume matching0.3 credits
company_job_listingsOne company, by name or domain0.3 credits
company_job_openingsOne company, by LinkedIn URL or domain0.3 credits

Use this one when you need detailed filtering. For a quick keyword sweep, linkedin_job_listings is simpler to prompt.


Parameters

Nothing is strictly required — pass at least keyword or locations. The optional set is grouped into six families.

ParameterTypeNotes
keywordarrayTitle keywords
locationsarrayCities, regions or countries
published_atstringr<seconds> window — r86400 past 24h, r604800 past week, r2592000 past month

Job

ParameterTypeNotes
job_typestringpart-time | internship | contract | full-time | temporary
work_typestringon-site | remote | hybrid
experience_levelstringentry-level | internship | associate | mid-senior | director
job_function_includeJob functions to keep
job_function_excludeJob functions to drop

Company

ParameterTypeNotes
company_excludeCompany names to drop
company_size_minnumberMinimum headcount
company_size_maxnumberMaximum headcount
company_founded_date_minEarliest founded date
company_founded_date_maxLatest founded date
company_followers_count_minnumberMinimum LinkedIn followers
company_followers_count_maxnumberMaximum LinkedIn followers
exclude_recruiting_agenciesbooleanDrop agency-posted roles
enrich_company_databooleanRicher company detail, slower

Quality

ParameterTypeNotes
salary_basestringe.g. "60000"
require_salary_infobooleanOnly openings that publish salary
filter_easy_applybooleanOnly Easy Apply openings
filter_under_10_applicantsbooleanOnly openings with fewer than 10 applicants
require_recruiter_profilebooleanOnly openings with a named recruiter

Matching

ParameterTypeNotes
resume_keywordsarrayArray of {keyword, aliases[]} — scores how well each job matches a resume

Output

ParameterTypeNotes
max_resultsnumber1–100, default 10
save_only_unique_itemsbooleanDrop duplicate openings

How to use it

Connect the MCP server

Follow the setup guide for your client. Browser sign-in, no API key.

Search with company filters

Search LinkedIn job openings for "RevOps" and "Revenue Operations" in London and Manchester. Companies between 50 and 500 employees, exclude recruiting agencies, posted in the past week. 50 results.

Add quality filters

Same search, but only openings that publish a salary and have a named recruiter on the post.

Score against a resume

Rerun with resume keywords for Salesforce, HubSpot, SQL and forecasting, then rank the openings by match score.

Example prompts

Ask your clientWhat you get back
”RevOps openings in London posted in the past 24 hours”published_at set to r86400
”Remote AE roles at companies under 200 people, no agencies”work_type, company_size_max, exclude_recruiting_agencies
”Openings with under 10 applicants and Easy Apply”Low-competition list
”Rank these openings against my resume skills”Match scores from resume_keywords

Best prompting practices

  • Always pass keyword or locations. Everything else is a filter on top of them.
  • Say the time window in words. “Posted in the past week” is enough — your client converts it to r604800. Only write the raw r<seconds> value if you want an exact window.
  • Exclude agencies for outbound. exclude_recruiting_agencies removes the reposted noise that ruins an account list.
  • Turn on enrich_company_data only when you need it. It is slower, and you may already have the firmographics from enrich_organization.
  • Use save_only_unique_items on wide searches. Multiple keywords across multiple cities will return the same opening more than once.

Output

{ "jobs": [ { "title": "Revenue Operations Lead", "company": "Stripe", "location": "London, United Kingdom", "posted_at": "2026-08-04", "url": "https://linkedin.com/jobs/view/1234567890" } ] }

Credits and limits

0.3 credits per call, flat, whatever filters you set. Maximum 100 openings per call. Run check_credits (free) before a long run of searches.

Stacking filters narrows results fast. If a search returns nothing, drop the quality filters first — require_salary_info and filter_under_10_applicants exclude most openings on their own.


ToolUse it instead when
linkedin_job_listingsA plain keyword search is enough — 0.3 credits
company_job_listingsYou want one company, by name or domain — 0.3 credits
company_job_openingsYou want one company and only have its LinkedIn URL — 0.3 credits
job_openings_growth_rateYou want the hiring trend over time, not the openings — 3 credits

Next steps

  • All MCP tools — the full catalogue with credit costs
  • Signals & ABM — workflows that turn hiring signals into an account list

Keep learning

Two courses take these tools past the reference page — clustered by GTM job, then chained into workflows.