
Google Jobs
io.github.johnisanerdv1.0.0更新於 Oct 6, 2026
Google Jobs listings with direct apply links via the Apify Google Jobs Scraper, hosted MCP.
概覽
讓助理搜尋 Google Jobs 職缺,並回傳附有直接應徵連結的結構化職缺紀錄。
- 功能
- 將 Apify Google Jobs Scraper 包裝成託管式 MCP 工具。它可依查詢字詞、地點、國家、語言與 Google 網域搜尋 Google Jobs,並支援地點半徑篩選與分頁控制。每筆結果是一筆職缺紀錄,包含職稱、公司、地點、來源平台、完整描述、資格與福利等結構化重點、解析後的中繼資料,以及跨平台的直接應徵連結。
- 適用情境
- 適合助理需要取得最新職缺刊登的情境,例如招募研究、市場或薪資分析,或建立附有應徵連結的職缺清單。較適合隨需搜尋,而非大規模持續爬取。
- 執行需求
- 使用 mcp.apify.com 上的遠端 MCP 端點,不需要本機執行環境。需要 Apify 帳號與 API 權杖,可透過瀏覽器 OAuth 提供,或以 Authorization Bearer 標頭使用 APIFY_API_TOKEN。需要能連線至該端點的網路。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Google Jobs,將其新增到工作區。
- 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。
其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"google-jobs": {
"type": "http",
"url": "https://mcp.apify.com/?tools=johnvc/Google-Jobs-Scraper"
}
}
}README
💼 Google Jobs API: Job Listings in Clean JSON
The most efficient, reliable, and developer-friendly way to use the Google Jobs API.
Actor page: apify.com/johnvc/Google-Jobs-Scraper Input schema: apify.com/johnvc/Google-Jobs-Scraper/input-schema
The Google Jobs API searches Google Jobs and returns clean, structured JSON, one record per listing. Each job includes title, company, location, source platform, the full description, structured highlights (qualifications, responsibilities, benefits), parsed metadata (posting date, schedule type, benefits), and direct apply links across platforms (LinkedIn, Indeed, company site, and more). Supports location targeting, location-radius search, country and language filtering, and pagination.
Looking for per-result pricing instead of per-page? See the pay-per-result edition.
Video Walkthrough
Quick Start
Prerequisites
- Python 3.11 or higher
- An Apify account and API key (get a free key here)
-
Clone the repository
-
Install dependencies with UV
-
Configure your API key
-
Run the example
Alternative: set the API key directly
Why Use This Google Jobs API?
One record per job, fully detailed. Every listing comes with title, company, location, source, the full description, structured highlights, and parsed metadata, so you can load it straight into an ATS, a dashboard, or an analysis pipeline.
Direct apply links. Each job includes apply options across platforms (LinkedIn, Indeed, the company careers site, and more) with direct URLs.
Targeted search. Filter by location, country, language, and Google domain, and use location-radius search to focus on a specific area.
Predictable, pay-per-use pricing. Billing is per page processed, with no subscription. You control cost with the page limit.
Easy to automate. Call it from Python in a few lines, or load it as an MCP tool so assistants like Claude and Cursor can search jobs for you on demand.
Features
Core Capabilities
- Job search with location, country, language, and Google-domain targeting
- Location-radius search to focus results on a specific area
- Pagination control with a configurable page cap
- Direct apply links across multiple platforms per job
- Structured highlights: qualifications, responsibilities, benefits
Data Quality
- One record per job with a stable structure
- Full description text plus parsed metadata (posting date, schedule type, benefits)
- Apply options with platform names and direct URLs
- Search metadata echoed on every record
- Consistent JSON shape across every query
Usage Examples
Basic search
Localized search with radius
Input Parameters
Output Format
A real result for Software Engineer in San Francisco (one item per job; the full description, job_highlights, extensions, and detected_extensions are present but omitted here for readability, and job_id is truncated).
Each job record also includes the full description text, a job_highlights array (qualifications, responsibilities, benefits), an extensions array of raw tags (for example Full-time), and a detected_extensions object with parsed fields like posting date and schedule type.
Use as an MCP tool
You can load the Google Jobs API as an MCP tool so assistants call it for you. The MCP server URL preloads just this one Actor:
Authenticate with OAuth in the browser when offered, or with your Apify API token (the same APIFY_API_TOKEN used by the Python example). Get a token at https://console.apify.com/settings/integrations and a free Apify account at https://apify.com?fpr=9n7kx3 .
Install in Claude Cowork Desktop
[Install in Claude Cowork Desktop]
Cowork is the desktop app's automation mode. To give it the Google Jobs API as a tool, add the Apify MCP server as a connector.
- Open the Claude desktop app and go to Settings → Connectors (or Settings → Developer → Edit Config to edit
claude_desktop_config.jsondirectly).- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
- Add the Apify MCP server, preloaded with only this Actor:
- 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.
- In a Cowork chat, confirm the tool is available and ask it to run the Google 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
Claude Code is the command-line tool. Add the Actor's MCP server with one command:
To use a token instead of browser OAuth:
Then verify with claude mcp list, or run /mcp inside a session. Ask Claude Code to call the Google 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)
On claude.ai you add Apify as a connector, then enable just this Actor's tool.
- Go to Settings → Connectors → Browse connectors and search for Apify MCP server. Install it (enable or update if prompted).
- When connecting, authenticate with your Apify API token, and enable the tool
johnvc/Google-Jobs-Scraper. - In any chat, open + → Connectors and turn on Apify.
- Alternatively, choose Add custom connector and paste the full MCP URL
https://mcp.apify.com/?tools=actors,docs,johnvc/Google-Jobs-Scraper, using OAuth when prompted. - Ask Claude to run the Google Jobs API.
Open Claude on the web: https://claude.ai/referral/uIlpa7nPLg
Install in Cursor
Cursor reads MCP servers from a project file at .cursor/mcp.json.
- In your project, create
.cursor/mcp.json:
- If you prefer token auth over browser OAuth, add a header:
- Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
- In Composer or Chat, ask Cursor to call the Google Jobs API.
New to Cursor? Get it here: https://cursor.com/referral?code=XQP4VBLI3NNX
Install in ChatGPT
ChatGPT connects to the Apify MCP server through Developer mode (available on ChatGPT Pro, Plus, Business, Enterprise, and Education plans).
- 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.
- Click Create app and fill out the form:
- Name: Apify
- MCP Server URL:
https://mcp.apify.com/?tools=actors,docs,johnvc/Google-Jobs-Scraper - Authentication: OAuth
- Click Create and authorize the connection with Apify.
- 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
Use the Google Jobs API to power recruiting tools, market research, and analytics with reliable, structured results.
🤖 Ask an AI assistant about this Actor
Open a ready-to-send prompt about the Google Jobs API in the AI of your choice:
- 💬 ChatGPT
- 🧠 Claude
- 🔍 Perplexity
- 🅒 Copilot
Last Updated: 2026.09.22
來源:README.md,提交 5651607
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1- v1.0.0最新Sep 16, 2026
