Mcp Linkedin Jobs Feed

com.mambabuiltPublished by mambabuilt.comv1.0.1Updated Nov 7, 2026

LinkedIn job search results with the employer website domain on every row. No login.

VerifiedSTDIODesktop onlyWeb Search & ScrapingBusiness & Commerce

Overview

AI-generated overview

Searches LinkedIn's public job listings by keyword and location and returns one row per job with the employer's website domain attached.

What you can do
  • Search LinkedIn jobs by keywords and locations, with filters for posting window, workplace type, experience level, job type and excluded companies
  • Return one row per job with title, company, company page, location, posting date, job link and the employer's website domain
  • Optionally read each job's public posting page for details
  • Return only jobs not seen in an earlier run with the same state key, for recurring schedules
  • Return a free summary row per search and location with jobs found and jobs returned
When to use it
Useful for recruiting, sales prospecting or market research where you want LinkedIn job postings turned into structured rows with company domains, including recurring daily or weekly sweeps of new postings.
Requirements
Runs locally via npx, so Node.js 18 or newer is needed. Requires an Apify account and an Apify API token set as the APIFY_TOKEN environment variable; the tool is listed without a token but calls need one. The work runs on Apify, so network access is required.
Before you install
Usage is billed per event to your Apify account (per job row plus a per-run start fee); max_charge_usd can cap a run. The APIFY_TOKEN is a secret and should not be shared. Results come from LinkedIn's public guest pages and employer domains are inferred by web search, so domains may be missing or labeled unresolved. Runs read public web pages and send search terms to Apify.

Installation

In SourceWeft

  1. Open Mcp Linkedin Jobs Feed in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

LinkedIn Jobs Feed MCP Server

[Glama score] [MCP Registry] [npm version] [npm downloads] [license] [mcpservers.org]

An MCP server for the Mamba Labs LinkedIn Jobs Feed actor on Apify. Give it job searches and locations. It returns one row per job from LinkedIn's public job search, with the employer's own website domain attached.

What's Inside

What it does

  • Source: LinkedIn's public guest job search and job posting pages only. No login, no cookie, no profile or company page reads.
  • Employer domain: a company name autocomplete, then a web search, once per employer and cached; returned only when the domain clearly matches the company name (domain_status resolved), otherwise empty and labeled.
  • Rows: one job row per job with the posting details, and one free search row per search and location with jobs_found and jobs_returned.
  • Filters and schedules: posted within, workplace type, experience level, job type, excluded companies, and only_new with a state_key.

All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.

Quick start

You need Node.js 18 or newer and an Apify account with an API token.

Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:

json
{  "mcpServers": {    "mamba-linkedin-jobs-feed": {      "command": "npx",      "args": [        "-y",        "@mambalabsdev/mcp-linkedin-jobs-feed"      ],      "env": {        "APIFY_TOKEN": "your-apify-token"      }    }  }}

Restart the client. The search_linkedin_jobs tool appears.

Prerequisites

Example prompts

  • "Find account executive jobs posted in Germany this week and give me the hiring companies' domains."
  • "Which companies in London posted a head of sales or SDR manager job in the last 24 hours?"
  • "Every morning, list new remote RevOps jobs in the United States with the company domain."

Tool

search_linkedin_jobs. One tool. Example arguments:

json
{  "keywords": [    "account executive"  ],  "locations": [    "Germany"  ],  "max_jobs_per_search": "5"}

Inputs

Every buyer facing input of the actor, unchanged. Omitted inputs take the actor's own defaults. Numbers and booleans are sent as strings.

InputTypeDescription
keywordsarrayOne job search per line, as you would type it in LinkedIn's job search, for example account executive, or sdr manager saas. Up to 50 searches per run (keywords times locations)
locationsarrayOptional. One location per line, as LinkedIn's job search takes it: a country (Germany), a city (London, England, United Kingdom), or a region (European Union). Each search runs once per location. Empty searches worldwide
posted_withinstringOnly jobs posted in this window, as LinkedIn dates them
workplace_typesarrayOptional. Any of: on_site, remote, hybrid
experience_levelsarrayOptional. Any of: internship, entry, associate, mid_senior, director, executive
job_typesarrayOptional. Any of: full_time, part_time, contract, temporary, internship, volunteer, other
max_jobs_per_searchstringJob rows returned per search, newest first. Default 100, up to 1000 (LinkedIn shows guests about 1,000 results per search)
exclude_companiesarrayOptional. Drop jobs whose company name contains one of these, ignoring case, for example staffing agencies you do not want
include_detailsstringtrue reads each job's public posting page. No extra charge
find_company_domainstringtrue looks up each employer's own website domain by name with a web search, and returns it only when the domain clearly matches the name. No extra charge
only_newstringtrue returns only jobs that an earlier run with the same state key did not return. The first run returns every job in the window
state_keystringNames the saved state for only new jobs. Use one key per schedule, for example ae-germany-daily
reset_statestringtrue forgets the saved state for this state key
max_charge_usdstringOptional. The run stops before it would charge more than this

Pricing

Pay per event on Apify, billed to your Apify account. Prices in USD.

EventFree planBronzeSilverGold
job-row, one job returned, with details and the employer domain$0.0015$0.001425$0.00135$0.001275
apify-actor-start, per run start$0.001$0.001$0.001$0.001

Search rows and the row for a refused input are free. Posting details and the domain lookup carry no extra charge.

Your keys

The actor needs no key and no LinkedIn account. It reads public job pages and a public search results page and holds no key of any kind. Mamba Labs pays the platform and proxy costs of the run.

Full actor documentation

apify.com/mambalabs/linkedin-jobs-feed

License

MIT. See LICENSE.

Source: README.md at commit de08149

Tools

1

search_linkedin_jobs

Search LinkedIn jobs with the employer domain

Search LinkedIn jobs by keywords and location and return one row per job with the employer's own website domain attached. Reads only LinkedIn's public guest job search and job posting pages, with no login. Each job row carries title, company, company page, location, posting date, job link, and by default the description, seniority level, employment type, job function, industries, and applicant count. The employer domain comes from a public company name autocomplete, then a web search, and is returned only when it clearly matches (domain_status resolved). Filters: posted within 24h, week, or month; workplace type; experience level; job type; excluded companies. only_new with a state_key returns only jobs earlier runs did not return. One free search row per search and location gives the counts. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN; Apify charges per job row returned and once per run start; search rows are free.

Parameterskeywordsonly_newjob_typeslocationsstate_keyreset_stateposted_withinmax_charge_usdinclude_detailsworkplace_typesexclude_companiesexperience_levels+2 more

Version history

2
  1. v1.0.1LatestNov 5, 2026
  2. v1.0.0Oct 30, 2026

Score

90% of the applicable checks met

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  • Reached in the last 30 days25 pts
  • Auth declared10 pts

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  • Tools listedRequired15 pts
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