Linkedin Jobs

io.github.johnisanerd由 GitHub 帳號 johnisanerd 發布v1.0.0更新於 Nov 5, 2026

LinkedIn jobs by keyword and location, with salary, description, and apply links, via hosted MCP.

已驗證Streamable HTTP可網頁執行網頁搜尋與抓取商業與電商

概覽

AI 產生的概覽

託管於 Apify 的 MCP 工具,讓助理依關鍵字與地點搜尋公開的 LinkedIn 職缺,並回傳薪資、描述、應徵連結等結構化資料。

可以做什麼
  • 依關鍵字、地點、國家或公司搜尋公開的 LinkedIn 職缺
  • 依資歷、僱用類型、遠端與刊登時間篩選,並可限制每次搜尋的職缺數量
  • 依網址擷取指定職缺,每次最多 1000 筆
  • 每筆職缺回傳一致的 JSON 資料,含職稱、公司、地點、薪資、描述、應徵連結與簡短摘要
適用情境
適合讓助理蒐集就業市場資料:招募流程、職缺與薪酬的市場研究,或從徵才訊號中開發潛在客戶,而不必自行建置爬取系統。
執行需求
透過 Apify MCP 伺服器連線至 mcp.apify.com 遠端端點;需要 Apify 帳號,使用 OAuth 登入或提供 Apify API 權杖作為 Bearer Authorization 標頭。README 中的本機 Python 範例另需 Python 3.11 以上與 APIFY_API_TOKEN 環境變數。
安裝前請注意
依回傳的職缺數量計費,範圍過大的搜尋會產生費用,建議以 maxJobs 限制數量。此工具只讀取公開的 LinkedIn 頁面,不會索取 LinkedIn 帳號或工作階段 Cookie。連線後助理可透過 OAuth 或權杖存取你的 Apify 帳號,職缺資料經 Apify 伺服器取得。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Linkedin Jobs,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.johnisanerd%2Flinkedin-jobs/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "linkedin-jobs": {
      "type": "http",
      "url": "https://mcp.apify.com/?tools=johnvc/linkedin-jobs-api"
    }
  }
}

README

💼 LinkedIn Jobs API: Job Listings to Structured JSON

The most efficient, reliable, and developer-friendly way to use the LinkedIn Jobs API.

Actor page: apify.com/johnvc/linkedin-jobs-api Input schema: apify.com/johnvc/linkedin-jobs-api/input-schema

Search public LinkedIn job listings by keyword, location, seniority, and job type, or fetch specific job posting URLs, and get back one clean JSON row per job: title, company, location, salary, seniority, employment type, apply link, and more. It is built API-first and MCP-ready, so you can call it from Python or drive it as a tool from an AI agent.

Video Walkthrough

[Watch the walkthrough]

Quick Start

Prerequisites

  1. Clone the repository

    bash
    git clone https://github.com/johnisanerd/Apify-LinkedIn-Jobs-API.gitcd Apify-LinkedIn-Jobs-API
  2. Install dependencies with UV

    bash
    # Install UV if you do not have it:curl -LsSf https://astral.sh/uv/install.sh | sh
    # Install project dependencies:uv sync
  3. Configure your API key

    bash
    cp .env.example .env# Edit .env and add your Apify API key# Get your free API key at: https://apify.com?fpr=9n7kx3
  4. Run the example

    bash
    uv run python linkedin-jobs-api-example.py

Alternative: set the API key directly

bash
export APIFY_API_TOKEN="your_api_key_here"uv run python linkedin-jobs-api-example.py

Why Use This LinkedIn Jobs API?

A search in, structured data out. You never touch collection infrastructure. Pass a keyword and location (or a list of job URLs) and get flat, predictable fields you can load straight into a sheet, a database, or an ATS.

Filter to exactly the roles you want. Narrow by seniority, job type, remote, company, and date posted, and cap each search with maxJobs so a broad query never overshoots your budget.

Pay per job. Billing is per job returned, with no per-run setup fee, so you only pay for what is delivered.

Reliable and predictable. Every job comes back with the same field shape, and an empty search returns a clear error row instead of failing the whole run.

MCP-ready. Call it as a tool from Claude, Cursor, and other AI agents (see the install sections below).

Features

Core Capabilities

  • Search public LinkedIn jobs by keyword, location, country, and company
  • Filter by seniority, employment type, remote, and date posted
  • Or fetch specific job postings directly by URL (up to 1000 per run)
  • Title, company, location, description, salary, and apply link on every row

Data Quality

  • One consistent JSON row per job, every time
  • A plain-language summary field on every row for quick scanning and AI use
  • A clear error row for an empty search, so one query never sinks the batch

Usage Examples

Basic Example

json
{  "keyword": "python developer",  "location": "New York",  "maxJobs": 5}

Filtered Example

json
{  "keyword": "product manager",  "location": "London",  "experienceLevel": "mid-senior",  "jobType": "full-time",  "remote": true,  "timeRange": "past-week",  "maxJobs": 50}

Fetch specific jobs by URL

json
{  "jobUrls": [    "https://www.linkedin.com/jobs/view/4286961888"  ]}

Input Parameters

ParameterTypeRequiredDefaultDescription
keywordstrone of these-Job title or keyword to search for, e.g. "python developer".
locationstrone of these-Location to search within, e.g. "New York" or "United Kingdom".
companystrone of these-Filter to a specific company name.
jobUrlslist[str]one of these-Specific LinkedIn job posting URLs. Up to 1000 per run.
countrystrNo-Two-letter country code to scope the search, e.g. "US", "GB".
jobTypestrNo-full-time, part-time, contract, temporary, internship, volunteer.
experienceLevelstrNo-internship, entry, associate, mid-senior, director, executive.
remoteboolNofalseReturn only remote jobs.
timeRangestrNo-past-day, past-week, past-month.
maxJobsintNo25Max jobs per search (max 500). Caps cost. Ignored for specific job URLs.

Supply a keyword, a location, a company, or at least one URL.

Output Format

Each job is returned as one JSON row:

json
{  "result_type": "job",  "jobId": "4286961888",  "jobUrl": "https://www.linkedin.com/jobs/view/4286961888",  "title": "Senior Python Developer",  "companyName": "GlossGenius",  "companyUrl": "https://www.linkedin.com/company/glossgenius",  "location": "New York, NY",  "seniorityLevel": "Mid-Senior level",  "employmentType": "Full-time",  "jobFunction": "Engineering and Information Technology",  "salary": "$150,000 - $190,000",  "postedDate": "2026-06-20",  "numApplicants": 47,  "applyUrl": "https://www.linkedin.com/jobs/view/4286961888/apply",  "summary": "Senior Python Developer, at GlossGenius, New York, NY, Full-time, $150,000 - $190,000"}

The salary field is returned when LinkedIn lists a pay range or base salary for the role.


FAQ

Will this put my LinkedIn or LinkedIn Recruiter account at risk?

No. It reads public LinkedIn pages only, the ones anyone can open while signed out. It never logs in and never asks for your cookies: there is no input for an account, a password or an li_at session cookie. Nothing it does is tied to your LinkedIn account, your LinkedIn Recruiter seat or your Sales Navigator license. The requests run on Apify's servers, not in your browser, so nothing connects them to you, and you can keep working in Recruiter while a run is going.


Install in Claude Cowork Desktop

[Install in Claude Cowork Desktop]

Cowork is the desktop app's automation mode. To give it the LinkedIn Jobs API as a tool, add the Apify MCP server as a connector.

  1. Open the Claude desktop app and go to Settings → Connectors (or Settings → Developer → Edit Config to edit claude_desktop_config.json directly).
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the Apify MCP server, preloaded with only this Actor:
json
{  "mcpServers": {    "apify": {      "command": "npx",      "args": [        "-y",        "mcp-remote",        "https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api"      ]    }  }}
  1. Restart the app. When Cowork first calls the tool, complete the OAuth prompt in your browser, or add your Apify API token in the connector settings to skip OAuth.
  2. In a Cowork chat, confirm the tool is available and ask it to run the LinkedIn Jobs API.

Download the desktop app and start a free trial: https://claude.ai/referral/uIlpa7nPLg More help: https://docs.apify.com/platform/integrations/claude-desktop


Install in Claude Code

[Install in Claude Code]

Claude Code is the command-line tool. Add the Actor's MCP server with one command:

bash
claude mcp add --transport http apify \  "https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api"

To use a token instead of browser OAuth:

bash
claude mcp add --transport http apify \  "https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api" \  --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Then verify with claude mcp list, or run /mcp inside a session. Ask Claude Code to call the LinkedIn Jobs API.

Try Claude Code free: https://claude.ai/referral/uIlpa7nPLg Claude Code MCP docs: https://code.claude.com/docs/en/mcp


Install in Claude (website)

[Install in Claude (website)]

On claude.ai you add Apify as a connector, then enable just this Actor's tool.

  1. Go to Settings → Connectors → Browse connectors and search for Apify MCP server. Install it (enable or update if prompted).
  2. When connecting, authenticate with your Apify API token, and enable the tool johnvc/linkedin-jobs-api.
  3. In any chat, open + → Connectors and turn on Apify.
  4. Alternatively, choose Add custom connector and paste the full MCP URL https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api, using OAuth when prompted.
  5. Ask Claude to run the LinkedIn Jobs API.

Open Claude on the web: https://claude.ai/referral/uIlpa7nPLg


Install in Cursor

[Install in Cursor]

Cursor reads MCP servers from a project file at .cursor/mcp.json.

  1. In your project, create .cursor/mcp.json:
json
{  "mcpServers": {    "apify": {      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api"    }  }}
  1. If you prefer token auth over browser OAuth, add a header:
json
{  "mcpServers": {    "apify": {      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api",      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }    }  }}
  1. Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
  2. In Composer or Chat, ask Cursor to call the LinkedIn Jobs API.

New to Cursor? Get it here: https://cursor.com/referral?code=XQP4VBLI3NNX


Install in ChatGPT

[Install in ChatGPT]

ChatGPT connects to the Apify MCP server through Developer mode (available on ChatGPT Pro, Plus, Business, Enterprise, and Education plans).

  1. Click your profile icon, then go to Settings > Apps. If you do not see a Create app button, open Advanced settings and enable Developer mode.
  2. Click Create app and fill out the form:
    • Name: Apify
    • MCP Server URL: https://mcp.apify.com/?tools=actors,docs,johnvc/linkedin-jobs-api
    • Authentication: OAuth
  3. Click Create and authorize the connection with Apify.
  4. To use the app in a conversation, click + in the chat, choose Developer mode, and select Apify.

More help: https://docs.apify.com/platform/integrations/mcp


Made with care

Use the LinkedIn Jobs API to power your recruiting, market research, and lead generation workflows with reliable, structured results.

🤖 Ask an AI assistant about this Actor

Open a ready-to-send prompt about the LinkedIn Jobs API in the AI of your choice:

Last Updated: 2026.10.27

來源:README.md,提交 e9c93de

工具

0
該伺服器需要登入,因此 SourceWeft 無法在沒有帳號的情況下讀取其工具,也未收錄。已連接帳號所能看到的內容可能因帳號及其權限而異。

版本歷史

1
  1. v1.0.0最新Nov 5, 2026

評分

已滿足適用檢查項的 75%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具15 分

    請讓伺服器在無憑證時回應 tools/list,或發布可在沙箱中無憑證啟動的軟體包。

  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

    請在儲存庫或註冊中心條目中宣告授權條款。