# Hacker News MCP Server (`automation-lab/hackernews-mcp-server`) Actor Query Hacker News data programmatically: search stories, get top posts, Ask HN, Show HN, jobs, comments, and user profiles via the free HN Algolia API. - **URL**: https://apify.com/automation-lab/hackernews-mcp-server.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 MCP Server Query **Hacker News** programmatically using the free [HN Algolia API](https://hn.algolia.com/api). Search stories, fetch top/front-page posts, Ask HN threads, Show HN projects, job listings, story comments, and user profiles — all without scraping, without a browser, and without an API key. Designed as an **MCP-first actor**: AI agents and LLM workflows can call it as a tool. Human users can run it directly on Apify with a simple JSON input. ### What does the Hacker News MCP Server do? 🔧 It exposes 7 tools wrapping the HN Algolia API: | Tool | What it returns | |------|----------------| | `search_stories` | Full-text search across all HN stories with optional date range | | `get_top_stories` | Current front-page/trending stories | | `get_ask_hn` | Recent Ask HN threads | | `get_show_hn` | Recent Show HN posts | | `get_jobs` | Latest HN job listings | | `get_story_comments` | Full comment tree for any story | | `get_user_profile` | User karma, bio, and account info | No proxy is needed — the Algolia API is public and free. Each run typically completes in under 3 seconds. ### Who is this for? **AI agent developers** building research pipelines that need live HN data. Feed trending stories into your LLM workflow, extract what tech topics are trending today, or pull discussion threads for analysis — all via a single tool call. **Researchers and analysts** tracking tech discourse. Pull Ask HN threads on a topic, compare what developers are discussing week over week, or find everyone who worked on a project from Show HN. **Recruiters and job seekers** monitoring HN hiring. The `get_jobs` tool pulls the latest "Who is Hiring?" thread posts and HN Startups listings without any browser automation. **Developers building with Apify** who want a reliable, cost-predictable HN data source with structured JSON output, scheduling, and webhook support. ### Why use Hacker News MCP Server? - ✅ **No API key or login required** — wraps the free public HN Algolia API - ✅ **7 distinct tools in one actor** — search, browse, comments, and users, all from one place - ✅ **MCP-native design** — call individual tools from Claude, Cursor, or any MCP client - ✅ **Structured JSON output** — consistent field names across all tools, ready for downstream processing - ✅ **Date range filtering** — search stories within specific time windows - ✅ **HTTP-only, no browser** — fast, cheap, and reliable (256 MB, ~2s average runtime) - ✅ **No scraping** — uses the official Algolia search index, so no anti-bot risk ### What data can you extract? **Stories (all story tools)** | Field | Description | |-------|-------------| | `objectID` | HN item ID | | `title` | Story title | | `url` | Link URL (external article or HN thread) | | `author` | HN username | | `points` | Upvotes | | `num_comments` | Comment count | | `created_at` | ISO 8601 timestamp | | `text` | Story body text (Ask HN / Show HN) | | `tags` | Algolia tags (`story`, `ask_hn`, `show_hn`, `job`, etc.) | **Comments (`get_story_comments`)** | Field | Description | |-------|-------------| | `type` | `comment` | | `text` | Comment body (may include HTML tags) | | `parent_id` | ID of parent comment or story | | `story_id` | Root story ID | | `author` | Commenter username | | `created_at` | Timestamp | **Users (`get_user_profile`)** | Field | Description | |-------|-------------| | `karma` | Karma points | | `about` | Bio/about text | | `created_at` | Account creation date | | `submission_count` | Number of submissions | | `comment_count` | Number of comments | ### How much does it cost to query Hacker News data? This actor uses **pay-per-event (PPE) pricing**: | Event | Free tier | Paid tiers | |-------|-----------|-----------| | Run start (one-time) | $0.005 | $0.0025–$0.005 | | Tool invocation | $0.002 | $0.0008–$0.002 | **Real-world cost examples:** - Search for 20 stories: **~$0.007** total - Fetch front-page stories (20 results): **~$0.007** - Pull 100 comments from a story: **~$0.007** (one tool call) - Run 100 searches per day: **~$0.70/day** With the free **$5 credit** on Apify's Free plan, you can run approximately **700 tool invocations** — enough to prototype any HN data workflow. ### How to query Hacker News data 1. Go to [Hacker News MCP Server on Apify Store](https://apify.com/automation-lab/hackernews-mcp-server) 2. Click **Try for free** 3. Set the **Tool** dropdown to your desired action (e.g., `search_stories`) 4. Fill in the relevant parameters (e.g., `query: "Rust programming"`) 5. Click **Start** and wait 2–5 seconds 6. View results in the **Dataset** tab as structured JSON **Example inputs for each tool:** ```json // Search recent stories about AI { "tool": "search_stories", "query": "LLM inference", "maxResults": 20, "sortBy": "date", "dateFrom": "2025-01-01T00:00:00Z" } ```` ```json // Get today's top HN stories { "tool": "get_top_stories", "maxResults": 30 } ``` ```json // Pull comments from a specific story { "tool": "get_story_comments", "storyId": 39234738, "maxResults": 50 } ``` ```json // Look up a user profile { "tool": "get_user_profile", "username": "pg" } ``` ### Input parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `tool` | string | ✅ Yes | — | Tool to invoke (see 7 tool names above) | | `query` | string | For `search_stories` | — | Search keyword or phrase | | `dateFrom` | string | No | — | ISO 8601 start date for `search_stories` filter | | `dateTo` | string | No | — | ISO 8601 end date for `search_stories` filter | | `storyId` | integer | For `get_story_comments` | — | HN story ID (numeric, from the item URL) | | `username` | string | For `get_user_profile` | — | HN username | | `maxResults` | integer | No | 20 | Max results to return (1–100) | | `sortBy` | string | No | `relevance` | Sort order: `relevance` or `date` | ### Output examples **`search_stories` / `get_top_stories` output item:** ```json { "type": "story", "objectID": "46990729", "title": "An AI agent published a hit piece on me", "url": "https://theshamblog.com/an-ai-agent-published-a-hit-piece-on-me/", "author": "scottshambaugh", "points": 2346, "num_comments": 951, "created_at": "2026-02-12T16:23:24Z", "text": null, "tags": ["story", "front_page"] } ``` **`get_story_comments` output item:** ```json { "type": "comment", "objectID": "47679234", "author": "throweraway", "text": "This is exactly why we need better tooling for...", "created_at": "2026-04-07T19:12:00.000Z", "parent_id": 47679121, "story_id": 47679121 } ``` **`get_user_profile` output item:** ```json { "type": "user", "objectID": "pg", "author": "pg", "karma": 157316, "about": "Bug fixer.", "created_at": "2006-10-09T18:21:51Z" } ``` ### Tips for best results - 💡 **Use `sortBy: "date"` with `dateFrom`** for real-time monitoring (e.g., past 24 hours) - 💡 **Keep `maxResults` ≤ 20** for fast runs; increase to 100 only when you need volume - 💡 **For `get_story_comments`**: very large threads (500+ comments) return up to `maxResults` comments from the top of the tree — the API uses BFS ordering - 💡 **Story IDs** appear in HN URLs: `https://news.ycombinator.com/item?id=39234738` → `storyId: 39234738` - 💡 **Schedule daily** with `get_top_stories` to build a trending-story feed - 💡 **Combine tools**: first call `search_stories` to find a story ID, then `get_story_comments` to pull the discussion ### Integrations **HN stories → Google Sheets** — schedule `get_top_stories` daily, connect the dataset via Apify's Google Sheets integration to track which stories went viral. Use the built-in dataset export (JSON, CSV, Excel). **HN jobs → Slack** — run `get_jobs` on a schedule, use Apify webhooks to post new listings to a `#hiring` Slack channel. Never miss a relevant startup job post. **HN search → Make/Zapier** — trigger a `search_stories` run whenever a topic keyword appears, and route results to Notion, Airtable, or a CRM. Useful for competitive monitoring (track mentions of your product or competitors). **AI research pipeline** — chain this actor with an LLM summarizer: pull Ask HN threads on a topic, send them to Claude/GPT for summarization, and generate a weekly digest. The structured JSON output maps cleanly to LLM context windows. **Webhooks** — configure Apify webhooks on run completion to stream new HN data to your backend in real time. ### Using the Apify API **Node.js (Apify client)** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('automation-lab/hackernews-mcp-server').call({ tool: 'search_stories', query: 'TypeScript 5.0', maxResults: 20, sortBy: 'date', }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` **Python** ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("automation-lab/hackernews-mcp-server").call(run_input={ "tool": "get_ask_hn", "maxResults": 10, }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["title"], item["points"]) ``` **cURL** ```bash curl -X POST \ "https://api.apify.com/v2/acts/automation-lab~hackernews-mcp-server/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "tool": "get_show_hn", "maxResults": 20 }' ``` ### Use with AI agents via MCP Hacker News MCP Server is available as a tool for AI assistants that support the [Model Context Protocol (MCP)](https://docs.apify.com/platform/integrations/mcp). Add the Apify MCP server to your AI client — this gives you access to all Apify actors, including this one: #### Setup for Claude Code ```bash claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/hackernews-mcp-server" ``` #### Setup for Claude Desktop, Cursor, or VS Code Add this to your MCP config file: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com?tools=automation-lab/hackernews-mcp-server" } } } ``` Your AI assistant will use OAuth to authenticate with your Apify account on first use. #### Example prompts Once connected, try asking your AI assistant: - "Use automation-lab/hackernews-mcp-server to search for HN stories about Rust programming from the last 30 days, sorted by date" - "Get the current top 20 stories from Hacker News front page and summarize the main themes" - "Pull the comments from HN story 47679121 and find the most upvoted technical critiques" Learn more in the [Apify MCP documentation](https://docs.apify.com/platform/integrations/mcp). ### Is it legal to query Hacker News data? Yes. This actor uses the **official HN Algolia API** (`https://hn.algolia.com/api/v1/`) which is a public, free, rate-limit-free API provided explicitly for programmatic access to Hacker News data. There is no scraping involved. Hacker News content is user-submitted and governed by [Y Combinator's terms of service](https://www.ycombinator.com/legal/). Respect the API's fair-use spirit: don't hammer it with thousands of requests per second, and attribute content to original authors when appropriate. This actor does not bypass any authentication, rate limiting, or access controls. ### FAQ **How fast is it?** Most runs complete in 1–3 seconds. The HN Algolia API is fast and globally distributed. The actor uses Node.js `fetch()` with no browser overhead. **How much does it cost for 100 searches?** About $0.70 ($0.005 start + $0.002 × 100 tool calls). With Apify's free $5 credit you can run roughly 700 tool invocations before needing a paid plan. **How is this different from the official HN Firebase API?** The official [HN Firebase API](https://github.com/HackerNews/API) requires fetching each item individually and has no search. The Algolia API (used here) supports full-text search, tag filtering, date range queries, and returns full hit lists in a single request. Much more practical for programmatic use. **Why do some stories have no `url` field?** Ask HN and some Show HN posts are self-posts (text only). For these, the URL points back to the HN thread itself. The `text` field contains the body. **Why did `get_story_comments` return only 1 item?** The story may be very old (pre-2012) or have been indexed without its comment tree by Algolia. The actor returns the story itself plus all comments it could retrieve. For older stories, the Algolia `/items/{id}` endpoint may have no `children` array. **The search returned fewer results than `maxResults`. Why?** The HN Algolia index may have fewer matching results than your limit, or the story was submitted very recently and not yet indexed. Try again in a few minutes for very fresh content. ### Other developer tools you might like - 🔗 [Bing Search Scraper](https://apify.com/automation-lab/bing-search-scraper) — scrape Bing web search results for any query - 🔗 [Bing News Scraper](https://apify.com/automation-lab/bing-news-scraper) — track news coverage on any topic - 🔗 [arXiv Scraper](https://apify.com/automation-lab/arxiv-scraper) — search and extract research papers from arXiv - 🔗 [JSON Schema Generator](https://apify.com/automation-lab/json-schema-generator) — generate JSON schemas from sample data - 🔗 [AI Tools Directory Scraper](https://apify.com/automation-lab/ai-tools-directory-scraper) — discover new AI tools and products # Actor input Schema ## `tool` (type: `string`): Which HN tool to invoke. Options: search\_stories, get\_top\_stories, get\_ask\_hn, get\_show\_hn, get\_jobs, get\_story\_comments, get\_user\_profile. ## `query` (type: `string`): Search term for search\_stories tool. E.g. 'TypeScript', 'AI agent', 'startup'. ## `dateFrom` (type: `string`): Filter stories created after this date. ISO 8601 format, e.g. 2024-01-01T00:00:00Z. ## `dateTo` (type: `string`): Filter stories created before this date. ISO 8601 format. ## `storyId` (type: `integer`): HN story ID for get\_story\_comments tool. E.g. 39234738. ## `username` (type: `string`): HN username for get\_user\_profile tool. E.g. 'pg', 'dang'. ## `maxResults` (type: `integer`): Maximum number of results to return (1–100). Default: 20. ## `sortBy` (type: `string`): Sort order for search results. 'relevance' (default for search) or 'date' (newest first). ## Actor input object example ```json { "tool": "search_stories", "query": "AI agents", "maxResults": 20, "sortBy": "relevance" } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "tool": "search_stories", "query": "AI agents" }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/hackernews-mcp-server").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 = { "tool": "search_stories", "query": "AI agents", } # Run the Actor and wait for it to finish run = client.actor("automation-lab/hackernews-mcp-server").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 '{ "tool": "search_stories", "query": "AI agents" }' | apify call automation-lab/hackernews-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/hackernews-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News MCP Server", "description": "Query Hacker News data programmatically: search stories, get top posts, Ask HN, Show HN, jobs, comments, and user profiles via the free HN Algolia API.", "version": "0.1", "x-build-id": "Wdk1FEFWAEAAihH25" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~hackernews-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-hackernews-mcp-server", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~hackernews-mcp-server/runs": { "post": { "operationId": "runs-sync-automation-lab-hackernews-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~hackernews-mcp-server/run-sync": { "post": { "operationId": "run-sync-automation-lab-hackernews-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "tool" ], "properties": { "tool": { "title": "🔧 Tool to call", "enum": [ "search_stories", "get_top_stories", "get_ask_hn", "get_show_hn", "get_jobs", "get_story_comments", "get_user_profile" ], "type": "string", "description": "Which HN tool to invoke. Options: search_stories, get_top_stories, get_ask_hn, get_show_hn, get_jobs, get_story_comments, get_user_profile." }, "query": { "title": "Search query", "type": "string", "description": "Search term for search_stories tool. E.g. 'TypeScript', 'AI agent', 'startup'." }, "dateFrom": { "title": "Date from (ISO 8601)", "type": "string", "description": "Filter stories created after this date. ISO 8601 format, e.g. 2024-01-01T00:00:00Z." }, "dateTo": { "title": "Date to (ISO 8601)", "type": "string", "description": "Filter stories created before this date. ISO 8601 format." }, "storyId": { "title": "Story ID", "type": "integer", "description": "HN story ID for get_story_comments tool. E.g. 39234738." }, "username": { "title": "Username", "type": "string", "description": "HN username for get_user_profile tool. E.g. 'pg', 'dang'." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of results to return (1–100). Default: 20.", "default": 20 }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "date" ], "type": "string", "description": "Sort order for search results. 'relevance' (default for search) or 'date' (newest first).", "default": "relevance" } } }, "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 } } } } } } } } } } ```