Linkedin Jobs

io.github.johnisanerd由 GitHub 账号 johnisanerd 发布v1.0.0更新于 Nov 5, 2026

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

已验证Streamable HTTP可网页运行网页搜索与抓取商业与电商

概览

AI 生成的概览

托管在 Apify 上的 MCP 工具,让助手按关键词和地点搜索公开的 LinkedIn 职位,并返回薪资、描述、申请链接等结构化数据。

可以做什么
  • 按关键词、地点、国家或公司搜索公开的 LinkedIn 职位
  • 按资历、雇佣类型、远程和发布时间筛选,并可限制每次搜索的职位数量
  • 按 URL 抓取指定职位,每次最多 1000 条
  • 每条职位返回一致的 JSON 记录,含标题、公司、地点、薪资、描述、申请链接和简短摘要
适用场景
适合让助手收集招聘市场数据:招聘流程、职位与薪酬的市场调研,或从招聘信号中挖掘潜在客户,而无需自建抓取系统。
运行要求
通过 Apify MCP 服务器访问 mcp.apify.com 远程端点;需要 Apify 账户,使用 OAuth 登录或提供 Apify API 令牌作为 Bearer Authorization 请求头。README 中的本地 Python 示例另需 Python 3.11 及以上和 APIFY_API_TOKEN 环境变量。
安装前请注意
按返回的职位数量计费,范围过大的搜索会产生费用,建议用 maxJobs 限制数量。该工具只读取公开的 LinkedIn 页面,不索取 LinkedIn 账号或会话 Cookie。连接后助手可通过 OAuth 或令牌访问你的 Apify 账户,职位数据经 Apify 服务器获取。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Linkedin Jobs,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.johnisanerd%2Flinkedin-jobs/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "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

来源:README.md,提交 e9c93de

工具

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该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

1
  1. v1.0.0最新Nov 5, 2026

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