# 🇮🇳 India Jobs Scraper — Listings, Salaries & Skills (`nexgendata/foundit-jobs-scraper`) Actor Live India job listings with salary bands, experience, skills and apply URLs — search by role + city, or watch for new postings. Sourced from Foundit (Monster India). - **URL**: https://apify.com/nexgendata/foundit-jobs-scraper.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Jobs - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 job listings This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## India Jobs Scraper — Listings, Salaries & Skills 🇮🇳 Live **India job listings** with salary bands, required experience, skill tags, company, location, and a direct apply URL — search by role and city, or run it on a schedule to catch **new postings** as they appear. Clean JSON out, no login, built for recruiters, job boards, market-comp analysts, and AI agents. Data sourced from **Foundit (Monster India)**. ### 📊 What you get One record per job listing: - `title`, `company_name`, `location` - `min_experience_years`, `max_experience_years` - `min_salary`, `max_salary`, `currency` (when the employer discloses them) - `skills` (array), `functions`, `industries`, `employment_types` - `is_urgently_hiring`, `freshness`, `posted_at` - `job_url` (direct apply link), `source`, `job_id`, `scraped_at` **~20 listings per $1.** A typical 25-result search costs about **$1.25.** ### 💵 Pricing Pay-per-result, no subscription: | Event | Price | |---|---| | Actor start | $0.005 (per GB RAM, min 1) | | **Job listing** | **$0.05 each** | | Watch-check (per scheduled watch run) | $0.05 | **Worked example:** a search returning 25 listings = 1 start ($0.005) + 25 × $0.05 = **≈ $1.26**. A daily watch run that finds 4 new postings = $0.05 watch-check + 4 × $0.05 = **$0.25**. ### ⏰ Watch mode — new-posting alerts Turn on **`watchMode`** and schedule it. The first run seeds a baseline and emits nothing; every later run emits **only new postings** since the last run (keyed on the stable Foundit job id). Feed it into Slack, a sheet, or an agent for a standing "new roles for my search" pipeline. ```json { "keyword": "data engineer", "location": "pune", "watchMode": true, "watchLabel": "de-pune" } ```` ### 🤖 Use with AI agents Returns clean JSON an agent can call directly. Example: *"Find remote senior Python roles in India posted this week and summarize the salary ranges."* Works with MCP tool-calling and agentic (x402) payment flows — no API key required. #### API ```bash curl -X POST "https://api.apify.com/v2/acts/foundit-jobs-scraper/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"keyword":"data analyst","location":"mumbai","maxResults":50}' ``` #### CLI ```bash apify call foundit-jobs-scraper --input '{"keyword":"devops","location":"bangalore","maxResults":100}' ``` ### 🔗 Related NexGenData actors - **linkedin-jobs-scraper** — the same job-listing schema for LinkedIn (global sibling). - **nse-bse-announcements** — India-listed company filings & announcements. - **mca-company-registry** — India company master data (CIN, capital, status). - **india-startup-funding-tracker** — India startup funding rounds. - **india-trademark-search** — Indian trademark records. - **gem-tenders-india** — Indian government tenders. ### ❓ FAQ **Where does the data come from?** Foundit's (Monster India) public job-search service. Buyers search "India jobs"; Foundit is the underlying source. **How fresh is it?** Real-time — new postings appear as Foundit publishes them; each row carries `posted_at` and `freshness`. **Does a blocked source bill me?** No. If Foundit is unreachable the run fails loud and charges nothing — you never pay for an empty "success". **Can I filter by experience?** Yes — set `minExperienceYears` to drop junior roles, and `keyword` + `location` to scope the search. *** Data sourced from public Foundit (Monster India) job listings. This actor is not affiliated with or endorsed by Foundit or Monster. For informational and recruitment-research use. # Actor input Schema ## `keyword` (type: `string`): Role or keyword to search (e.g. 'python developer', 'data analyst', 'sales manager'). ## `location` (type: `string`): City or region in India (e.g. 'bangalore', 'mumbai', 'remote'). Leave empty for all-India. ## `minExperienceYears` (type: `integer`): Drop listings whose max experience is below this many years. ## `maxResults` (type: `integer`): Maximum job listings to return (1-500). ## `watchMode` (type: `boolean`): First run seeds a baseline and emits nothing; later runs emit only NEW postings since the last run (keyed on Foundit job id). Ideal on a schedule. ## `watchLabel` (type: `string`): Names the watch baseline so multiple saved tasks keep independent state. ## Actor input object example ```json { "keyword": "python developer", "location": "bangalore", "maxResults": 25, "watchMode": false, "watchLabel": "default" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keyword": "python developer", "location": "bangalore", "maxResults": 25 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/foundit-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keyword": "python developer", "location": "bangalore", "maxResults": 25, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/foundit-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keyword": "python developer", "location": "bangalore", "maxResults": 25 }' | apify call nexgendata/foundit-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/foundit-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🇮🇳 India Jobs Scraper — Listings, Salaries & Skills", "description": "Live India job listings with salary bands, experience, skills and apply URLs — search by role + city, or watch for new postings. Sourced from Foundit (Monster India).", "version": "0.0", "x-build-id": "ytqsWZOJ4OA3ZLV1U" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~foundit-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-foundit-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~foundit-jobs-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-foundit-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~foundit-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-foundit-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "keyword": { "title": "Job keyword / role", "type": "string", "description": "Role or keyword to search (e.g. 'python developer', 'data analyst', 'sales manager')." }, "location": { "title": "Location (optional)", "type": "string", "description": "City or region in India (e.g. 'bangalore', 'mumbai', 'remote'). Leave empty for all-India." }, "minExperienceYears": { "title": "Minimum experience (years, optional)", "type": "integer", "description": "Drop listings whose max experience is below this many years." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum job listings to return (1-500).", "default": 25 }, "watchMode": { "title": "Watch mode (new postings only)", "type": "boolean", "description": "First run seeds a baseline and emits nothing; later runs emit only NEW postings since the last run (keyed on Foundit job id). Ideal on a schedule.", "default": false }, "watchLabel": { "title": "Watch label", "type": "string", "description": "Names the watch baseline so multiple saved tasks keep independent state.", "default": "default" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```