# Hacker News Algolia Search by Query + Tags (`v0iddo/hn-algolia-search`) Actor Search Hacker News via the free Algolia API. One row per hit: title, author, points, num\_comments, URL, tags, story id. Filter by tags (`story`, `front_page`, `show_hn`, `ask_hn`, `author_xxx`, `story_xxx`) and an optional date window. For trend trackers, sentiment analysts, launch monitoring. - **URL**: https://apify.com/v0iddo/hn-algolia-search.md - **Developed by:** [vøiddo](https://apify.com/v0iddo) (community) - **Categories:** Business, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.10 / 1,000 hn story / comment extracteds 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 Algolia Search by Query + Tags Search Hacker News via the public Algolia API — the same data behind `https://hn.algolia.com/`. One row per hit, paginated, server-side date-filtered. Works for stories, comments, Ask HN, Show HN, polls, front page, by author, comments under a specific story. ### What you get ```` { "objectID": "37412345", "storyId": "37412345", "title": "Show HN: Notion-style outliner in 200 lines of JS", "author": "jane\_doe", "url": "https://github.com/jane\_doe/outliner", "points": 842, "numComments": 217, "createdAt": "2026-05-30T14:23:01.000Z", "createdAtUnix": 1781098981, "tags": \["show\_hn", "story", "author\_jane\_doe"], "permalink": "https://news.ycombinator.com/item?id=37412345", "query": "Show HN" } ```` ### How to use **Input.** ```json { "queries": ["Show HN: AI", "Ask HN: hiring"], "tags": ["story"], "sinceDays": 30, "maxResultsPerQuery": 500, "sortBy": "date" } ```` **Tag cheat sheet.** Tags are AND-ed: - `story` — only stories - `comment` — only comments - `front_page` — currently on the front page - `show_hn`, `ask_hn`, `poll` — special story types - `author_` — by author, e.g. `author_pg` - `story_` — all comments under a specific story **Common recipes.** - **"Last 24h Show HN top voters":** `queries=[""]`, `tags=["show_hn"]`, `sinceDays=1`, `sortBy=date`. - **"Front page right now":** `queries=[""]`, `tags=["front_page"]`, `sinceDays=1`. - **"Everyone talking about Anthropic this month":** `queries=["Anthropic"]`, `tags=["story", "comment"]`, `sinceDays=30`. - **"All comments under HN ID 37412345":** `queries=[""]`, `tags=["story_37412345"]`, `sinceDays=0`. ### Pricing PAY\_PER\_EVENT · `$0.0003 per story_extracted` · 3 333 hits = $1. ### Buyer - Launch trackers (Show HN sentiment for week's biggest dev tools). - Brand monitoring (every mention of your company on HN this month). - Hiring-signal radar (Ask HN: Who is hiring? threads). - Researchers studying HN community trends. ### Source `https://hn.algolia.com/api/v1/search` and `/search_by_date` — Algolia serves the entire HN index for free. No auth, no rate limit documented; this actor still paces 0.2s between pages. # Actor input Schema ## `queries` (type: `array`): Full-text queries. Leave empty + use `tags` for a tag-only feed (e.g. `front_page` + sinceDays=1 = last 24h front page). ## `tags` (type: `array`): HN Algolia tags: `story`, `comment`, `front_page`, `show_hn`, `ask_hn`, `poll`, `author_`, `story_`. Multiple tags AND together. ## `sinceDays` (type: `integer`): Server-side date filter via `created_at_i>UNIX`. Set 0 for no date filter (full history). ## `maxResultsPerQuery` (type: `integer`): Hard cap per query. Algolia paginates 100/page. ## `sortBy` (type: `string`): `date` = newest first (uses `/search_by_date`). `relevance` = Algolia ranking (uses `/search`). ## Actor input object example ```json { "queries": [ "Show HN: AI" ], "tags": [ "story" ], "sinceDays": 30, "maxResultsPerQuery": 500, "sortBy": "date" } ``` # 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 = { "queries": [ "Show HN: AI" ] }; // Run the Actor and wait for it to finish const run = await client.actor("v0iddo/hn-algolia-search").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 = { "queries": ["Show HN: AI"] } # Run the Actor and wait for it to finish run = client.actor("v0iddo/hn-algolia-search").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 '{ "queries": [ "Show HN: AI" ] }' | apify call v0iddo/hn-algolia-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=v0iddo/hn-algolia-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Algolia Search by Query + Tags", "description": "Search Hacker News via the free Algolia API. One row per hit: title, author, points, num_comments, URL, tags, story id. Filter by tags (`story`, `front_page`, `show_hn`, `ask_hn`, `author_xxx`, `story_xxx`) and an optional date window. For trend trackers, sentiment analysts, launch monitoring.", "version": "0.1", "x-build-id": "mezIoQUI4Hawjpabf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/v0iddo~hn-algolia-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-v0iddo-hn-algolia-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/v0iddo~hn-algolia-search/runs": { "post": { "operationId": "runs-sync-v0iddo-hn-algolia-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/v0iddo~hn-algolia-search/run-sync": { "post": { "operationId": "run-sync-v0iddo-hn-algolia-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "queries": { "title": "Search queries", "type": "array", "description": "Full-text queries. Leave empty + use `tags` for a tag-only feed (e.g. `front_page` + sinceDays=1 = last 24h front page).", "items": { "type": "string" } }, "tags": { "title": "Algolia tags filter", "type": "array", "description": "HN Algolia tags: `story`, `comment`, `front_page`, `show_hn`, `ask_hn`, `poll`, `author_`, `story_`. Multiple tags AND together.", "default": [ "story" ], "items": { "type": "string" } }, "sinceDays": { "title": "Window — last N days", "minimum": 0, "maximum": 3650, "type": "integer", "description": "Server-side date filter via `created_at_i>UNIX`. Set 0 for no date filter (full history).", "default": 30 }, "maxResultsPerQuery": { "title": "Max results per query", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Hard cap per query. Algolia paginates 100/page.", "default": 500 }, "sortBy": { "title": "Sort order", "enum": [ "date", "relevance" ], "type": "string", "description": "`date` = newest first (uses `/search_by_date`). `relevance` = Algolia ranking (uses `/search`).", "default": "date" } } }, "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 } } } } } } } } } } ```