# Hacker News Who is Hiring Company Leads (`scrapemint/hn-hiring-company-leads`) Actor Parse the monthly Hacker News Who is Hiring thread into B2B leads: company, role, location, remote flag, salary, apply email, apply URL, and website. One lead per post. Keyless HN API. - **URL**: https://apify.com/scrapemint/hn-hiring-company-leads.md - **Developed by:** [Ken M](https://apify.com/scrapemint) (community) - **Categories:** Business, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Hacker News Who is Hiring Company Leads Turn the monthly Hacker News "Who is hiring?" thread into a B2B lead list. Each post becomes one lead: company, role, location, remote flag, salary, **apply email**, apply URL, and company website. Companies posting on HN are actively hiring engineers, which is a strong growth signal. The thread is public and read through the keyless HN API. ### Who buys this - **Recruiting and sourcing SaaS** targeting companies that are hiring. - **Developer-tool and dev-service vendors** selling to engineering teams. - **Sales teams** using "actively hiring" as a buying signal. ### How it works 1. It finds the recent "Who is hiring?" threads from the HN `whoishiring` account. 2. It reads each top-level post and parses the company, role, location, remote flag, salary, apply email, and apply URL. 3. Each post is scored and tiered, then pushed as one lead. ### Output One row per post: ```json { "company": "Marker Learning", "role": "Lead Full-Stack Engineer", "location": "Remote (U.S. only)", "remote": true, "salary": "$160k-$190k", "applyEmail": "lucie@markerlearning.com", "applyUrl": "https://markerlearning.com/careers", "website": "https://markerlearning.com", "month": "June 2026", "hnCommentUrl": "https://news.ycombinator.com/item?id=...", "tier": "qualified_lead", "leadScore": 80 } ```` ### Tiers and pricing Pay per lead. The first 10 `qualified_lead` per run are free so you can validate output. | Tier | Meaning | Price | | --- | --- | --- | | `listing` | Post with company/role but no apply email or URL | $0.01 | | `lead` | An apply URL or company website | $0.02 | | `qualified_lead` | A direct apply email | $0.05 | The HN API is keyless, so runs are fast and cheap. ### Input | Field | Default | Notes | | --- | --- | --- | | `months` | `1` | How many recent threads to include. | | `keywords` | `[]` | Filter posts by text (rust, react, ml, senior, etc.). | | `remoteOnly` | `false` | Keep only remote posts. | | `requireEmail` | `false` | Only keep posts with an apply email. | | `maxLeads` | `500` | Cap total leads per run. | ### Notes - Posts are free text, so the company, role, and location are parsed from the conventional pipe-delimited first line; some posts give an apply URL or careers page instead of a direct email. - Respect HN's terms and applicable outreach laws when contacting companies. # Actor input Schema ## `months` (type: `integer`): How many recent 'Who is hiring' threads to include (1 = latest month). ## `keywords` (type: `array`): Filter posts by text match (e.g. rust, react, ml, senior, fintech). Empty keeps all. ## `remoteOnly` (type: `boolean`): Keep only posts that mention remote. ## `requireEmail` (type: `boolean`): Skip posts that do not include a contact email. ## `maxLeads` (type: `integer`): Cap total leads per run. ## `concurrency` (type: `integer`): Comments fetched in parallel. ## Actor input object example ```json { "months": 1, "keywords": [], "remoteOnly": false, "requireEmail": false, "maxLeads": 500, "concurrency": 10 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrapemint/hn-hiring-company-leads").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 = {} # Run the Actor and wait for it to finish run = client.actor("scrapemint/hn-hiring-company-leads").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 '{}' | apify call scrapemint/hn-hiring-company-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapemint/hn-hiring-company-leads", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Who is Hiring Company Leads", "description": "Parse the monthly Hacker News Who is Hiring thread into B2B leads: company, role, location, remote flag, salary, apply email, apply URL, and website. One lead per post. Keyless HN API.", "version": "0.1", "x-build-id": "uupC0hyCQt5QkOMTl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapemint~hn-hiring-company-leads/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapemint-hn-hiring-company-leads", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapemint~hn-hiring-company-leads/runs": { "post": { "operationId": "runs-sync-scrapemint-hn-hiring-company-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapemint~hn-hiring-company-leads/run-sync": { "post": { "operationId": "run-sync-scrapemint-hn-hiring-company-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "months": { "title": "Number of recent months", "minimum": 1, "maximum": 12, "type": "integer", "description": "How many recent 'Who is hiring' threads to include (1 = latest month).", "default": 1 }, "keywords": { "title": "Keywords", "type": "array", "description": "Filter posts by text match (e.g. rust, react, ml, senior, fintech). Empty keeps all.", "default": [], "items": { "type": "string" } }, "remoteOnly": { "title": "Remote only", "type": "boolean", "description": "Keep only posts that mention remote.", "default": false }, "requireEmail": { "title": "Only posts with an apply email", "type": "boolean", "description": "Skip posts that do not include a contact email.", "default": false }, "maxLeads": { "title": "Max leads", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Cap total leads per run.", "default": 500 }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 30, "type": "integer", "description": "Comments fetched in parallel.", "default": 10 } } }, "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 } } } } } } } } } } ```