# Hacker News Search & Monitor (`scrapeworks/hacker-news-search`) Actor Search and monitor Hacker News stories, comments, Ask HN, Show HN, jobs and users. No auth, clean structured JSON. Filter by points, date, author, and tags. - **URL**: https://apify.com/scrapeworks/hacker-news-search.md - **Developed by:** [Nicolas van Arkens](https://apify.com/scrapeworks) (community) - **Categories:** News, Other, Open source - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 results 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.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 Search & Monitor ๐Ÿ”Ž Search and monitor **Hacker News** โ€” stories, comments, Ask HN, Show HN, jobs, polls, and users โ€” and get clean, structured JSON. No login, no API key, no proxies required. Built on the free official Algolia HN Search index, so it's fast and reliable. Use it to **track mentions of your company, product, or competitors**, find **Show HN / Ask HN** discussions, monitor a topic over time, or build a Hacker News dataset for research and LLM pipelines. ### What you can do - ๐Ÿ” **Keyword search** across all of Hacker News (titles, self-text, and comments) - ๐Ÿ†• **Monitor by date** โ€” get the most recent matching items first, perfect for alerts and brand monitoring - ๐ŸŽฏ **Filter** by content type (story, comment, Ask HN, Show HN, job, poll), minimum points, minimum comments, author, and date range - ๐Ÿงน **Clean output** โ€” one tidy record per item with direct links to both the source URL and the HN discussion - โšก **Fast & lightweight** โ€” pure API, no headless browser ### Example use cases - **Brand / competitor monitoring:** search your company name sorted by date, schedule it daily, and pipe new mentions to Slack, email, or a sheet. - **Lead & trend research:** find the highest-scoring stories about a technology or market in a date window. - **Show HN / Ask HN discovery:** surface new launches or questions in your niche. - **Datasets for AI:** pull thousands of HN comments on a topic for sentiment analysis or RAG. ### Input | Field | Description | |-------|-------------| | **Search query** | Keyword(s) to search for. Leave empty to fetch the latest items by date (feed monitoring). | | **Content type** | Stories, Comments, Ask HN, Show HN, Polls, Jobs, or All. | | **Sort by** | Relevance (points & comments) or Date (most recent first). | | **Maximum items** | Total items to return; paginates automatically. | | **Minimum points / comments** | Only return stories above a threshold. | | **Author** | Restrict to a single HN username. | | **Created after / before** | Date range filter (YYYY-MM-DD). | | **Include full text** | Include comment/self-post body text, or keep it metadata-only. | ### Output Each item is returned as a record like this: ```json { "id": "48126840", "type": "story", "title": "A Great Essay", "url": "https://example.com/essay", "author": "pg", "points": 412, "numComments": 233, "createdAt": "2026-05-13T20:11:17Z", "createdAtTimestamp": 1778703077, "storyId": 48126840, "hnUrl": "https://news.ycombinator.com/item?id=48126840", "authorUrl": "https://news.ycombinator.com/user?id=pg", "text": null } ```` Export to JSON, CSV, or Excel, or pull results via the Apify API. Connect to Slack, Google Sheets, Zapier, or Make for automated monitoring. ### How it works This actor queries the public Algolia Hacker News Search API (`hn.algolia.com/api/v1`), the same index that powers HN's own search. It paginates through results, applies your filters server-side where possible, normalizes every item into a consistent schema, and stores it in your dataset. It does not require โ€” and never asks for โ€” any credentials. ### Notes - This actor accesses only publicly available Hacker News data via a free public API. It is an independent tool and is not affiliated with Y Combinator or Hacker News. - Algolia caps results at the most recent/relevant matches per query; for very large historical pulls, narrow by date range and run in windows. # Actor input Schema ## `query` (type: `string`): Keyword(s) to search for across Hacker News. Leave empty to fetch the latest/front-page items by date without a keyword filter (useful for monitoring a feed). ## `contentType` (type: `string`): Which kind of items to return. ## `sortBy` (type: `string`): Relevance ranks by points & comments (best for discovery). Date returns most recent first (best for monitoring/alerts). ## `maxItems` (type: `integer`): How many items to return in total. The actor paginates automatically. ## `minPoints` (type: `integer`): Only return stories with at least this many points. Leave empty for no minimum. (Applies to stories; comments do not have points.) ## `minComments` (type: `integer`): Only return stories with at least this many comments. Leave empty for no minimum. ## `author` (type: `string`): Only return items written by this Hacker News username (e.g. 'pg'). Leave empty for all authors. ## `createdAfter` (type: `string`): Only return items created on or after this date. Format: YYYY-MM-DD. ## `createdBefore` (type: `string`): Only return items created before this date. Format: YYYY-MM-DD. ## `includeCommentText` (type: `boolean`): Include the full body text of comments and self-posts. Turn off for a lighter, metadata-only dataset. ## Actor input object example ```json { "query": "AI", "contentType": "story", "sortBy": "relevance", "maxItems": 100, "includeCommentText": true } ``` # 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 = { "query": "AI" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeworks/hacker-news-search").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "query": "AI" } # Run the Actor and wait for it to finish run = client.actor("scrapeworks/hacker-news-search").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "query": "AI" }' | apify call scrapeworks/hacker-news-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeworks/hacker-news-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Search & Monitor", "description": "Search and monitor Hacker News stories, comments, Ask HN, Show HN, jobs and users. No auth, clean structured JSON. Filter by points, date, author, and tags.", "version": "0.1", "x-build-id": "cXEyaDiRTy6DH0ZAh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeworks~hacker-news-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeworks-hacker-news-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeworks~hacker-news-search/runs": { "post": { "operationId": "runs-sync-scrapeworks-hacker-news-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeworks~hacker-news-search/run-sync": { "post": { "operationId": "run-sync-scrapeworks-hacker-news-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "query": { "title": "Search query", "type": "string", "description": "Keyword(s) to search for across Hacker News. Leave empty to fetch the latest/front-page items by date without a keyword filter (useful for monitoring a feed)." }, "contentType": { "title": "Content type", "enum": [ "story", "comment", "ask_hn", "show_hn", "poll", "job", "all" ], "type": "string", "description": "Which kind of items to return.", "default": "story" }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "date" ], "type": "string", "description": "Relevance ranks by points & comments (best for discovery). Date returns most recent first (best for monitoring/alerts).", "default": "relevance" }, "maxItems": { "title": "Maximum items", "minimum": 1, "maximum": 10000, "type": "integer", "description": "How many items to return in total. The actor paginates automatically.", "default": 100 }, "minPoints": { "title": "Minimum points", "minimum": 0, "type": "integer", "description": "Only return stories with at least this many points. Leave empty for no minimum. (Applies to stories; comments do not have points.)" }, "minComments": { "title": "Minimum comments", "minimum": 0, "type": "integer", "description": "Only return stories with at least this many comments. Leave empty for no minimum." }, "author": { "title": "Author username", "type": "string", "description": "Only return items written by this Hacker News username (e.g. 'pg'). Leave empty for all authors." }, "createdAfter": { "title": "Created after", "type": "string", "description": "Only return items created on or after this date. Format: YYYY-MM-DD." }, "createdBefore": { "title": "Created before", "type": "string", "description": "Only return items created before this date. Format: YYYY-MM-DD." }, "includeCommentText": { "title": "Include full comment/story text", "type": "boolean", "description": "Include the full body text of comments and self-posts. Turn off for a lighter, metadata-only dataset.", "default": true } } }, "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 } } } } } } } } } } ```