# Threads Search & Monitor - Keyword Tracking + Contacts (`constructive_calm/threads-search-monitor`) Actor Search Threads by keyword/hashtag and monitor saved searches for new posts on a schedule. Optional reply trees + author bio contacts (email/phone). Cookie-free, no login. - **URL**: https://apify.com/constructive\_calm/threads-search-monitor.md - **Developed by:** [Omar Eldeeb](https://apify.com/constructive_calm) (community) - **Categories:** Social media, Lead generation, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.50 / 1,000 search 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 ## Threads Search & Monitor — Keyword Tracking + Contacts Search [Threads](https://www.threads.com) by keyword or hashtag, **monitor saved searches for new posts on a schedule**, and optionally pull full reply trees and author bio contacts (email/phone) — all in one actor. Cookie-free, no login, no tokens to maintain. Runs on the [Apify](https://apify.com) platform; export to JSON, CSV, or Excel, or pull straight from the API. It's the only Threads search actor on the Store with a **dedup-aware monitor mode**: schedule it and every run returns only the posts it hasn't seen before. --- ### What does Threads Search & Monitor do? Give it one or more keywords or hashtags and it returns the matching public Threads posts — author, text, engagement counts (likes / replies / reposts / quotes), media URLs, timestamp, and a deep link to each post. Three modes: - **Search** — keyword / phrase query, gathered across Threads' relevance *and* recency views for wider coverage per term. - **Hashtag** — tag feeds, same wide-coverage gathering. - **Monitor** — re-run your saved searches/hashtags on a schedule and get only the **new** posts since the last run (dedup-aware, persisted across runs). Two optional enrichments no other Threads search actor bundles: - **Reply trees on results** — pull the top discussion replies under each surfaced post (depth-aware). - **Author bio contacts** — resolve email / phone / links from each unique author's bio (great for lead-gen), deduped so you're charged once per author. ### Why use Threads Search & Monitor? - **Social listening teams & agencies** — track brand, competitor, and topic keywords now that Threads has opened ads to all advertisers and crossed 450M+ monthly users. Schedule the monitor and never re-pull the same post. - **Market & trend researchers** — gather the relevance + recency union per term, filter by date, export clean structured rows. - **Lead-gen & outreach** — find posts on your topic, then resolve the authors' bio contacts in the same run. - **AI / dataset builders** — collect topical public posts (and their discussions) as clean JSON for training and retrieval. - **No maintenance moat** — uses Meta's public social-bot SSR, so there are no rotating `doc_id`s, login cookies, or tokens to break. Reliable by design. ### How to use Threads Search & Monitor 1. Click **Try for free** / **Start**. 2. Pick a **Mode** (Search, Hashtag, or Monitor). 3. Enter your **search queries** and/or **hashtags**. 4. (Optional) Turn on **Include reply trees** and/or **Resolve author bio contacts**; set a **date window** and **Max items**. 5. For hands-off monitoring: set Mode = **Monitor**, then attach an **Apify Schedule** (e.g. hourly/daily). Each run appends only new posts. 6. Run it, then **export** the dataset as JSON / CSV / Excel, or read it from the API. ### Input **Search a keyword (wide coverage):** ```json { "mode": "search", "searchQueries": ["threads api", "social listening"], "sort": "top", "maxResultsPerQuery": 50 } ```` **Monitor hashtags on a schedule (only new posts each run):** ```json { "mode": "monitor", "hashtags": ["bitcoin", "ai"], "maxResultsPerQuery": 50 } ``` **Search + reply trees + author contacts (lead-gen):** ```json { "mode": "search", "searchQueries": ["dtc brand"], "includeReplies": true, "maxReplyDepth": 2, "resolveContacts": true, "resolveLinktree": true, "maxItems": 300 } ``` **Search a date window:** ```json { "mode": "search", "searchQueries": ["world cup"], "dateFrom": "2026-05-01", "dateTo": "2026-06-01" } ``` ### Output One post row (replies and author-contact rows share the same dataset, distinguished by `recordType`): ```json { "recordType": "post", "matchedQuery": "threads api", "postId": "3904856121039465368", "code": "DZFe09QgoGI", "url": "https://www.threads.com/@example/post/DZFe09QgoGI", "username": "example", "fullName": "Example User", "text": "Shipping a new Threads integration today…", "takenAt": "2026-06-12T14:23:51.000Z", "likeCount": 412, "replyCount": 37, "repostCount": 8, "quoteCount": 3, "mediaType": "image", "mediaUrls": ["https://…"], "serpTypes": ["default", "recent"], "fetchedAt": "2026-06-13T09:00:00.000Z", "sourceUrl": "https://www.threads.com/search?q=threads%20api&serp_type=default" } ``` **Reply row** (`recordType: "reply"`): adds `depth`, `parentPostId`, `replyToAuthor`. **Author row** (`recordType: "author"`, when `resolveContacts` is on): `biography`, `followerCount`, `isVerified`, `bioLinks`, `extractedEmails`, `extractedPhones`, `matchedQueries`. | Field | Description | |-------|-------------| | `recordType` | `post` | `reply` | `author` | | `matchedQuery` | Which search keyword / hashtag surfaced this row | | `serpTypes` | Which view(s) the post appeared in (`default` = relevance, `recent` = newest) | | `username` / `fullName` | Author identity | | `text` | Post body | | `takenAt` | Post timestamp (ISO) | | `likeCount` / `replyCount` / `repostCount` / `quoteCount` | Engagement | | `mediaType` / `mediaUrls` | `text` | `image` | `carousel` | `video` + best-resolution URLs | | `depth` / `parentPostId` / `replyToAuthor` | Reply linkage (reply rows) | | `extractedEmails` / `extractedPhones` / `bioLinks` | Author contacts (author rows) | | `url` | Canonical deep link to the post | ### How much does it cost to scrape Threads? Pay-per-event — you pay for what you pull: | Event | Price | When it fires | |-------|-------|---------------| | **Search result** | **$0.0025** | Per post surfaced for a query/hashtag (primary) | | Reply fetched | $0.0015 | Per reply, only when *Include reply trees* is on | | Monitor delta detected | $0.005 | Per new post in monitor mode | | Author bio contact resolved | $0.02 | Once per unique author, only when *Resolve contacts* is on | **The first 10 chargeable events of every run are free** — try it on a real query before paying. Typical runs: - 50 search results: ~**$0.13** (under $2.50 / 1,000 posts — cheaper than every comparable Threads search actor). - 50 results + their reply trees (~15 replies each): ~$0.13 + ~$1.10 replies. - Monitor 5 hashtags, ~20 new posts/run: ~**$0.10** per scheduled run. - 30 results + contacts on 25 unique authors: ~$0.075 + ~$0.50 contacts. ### Tips & advanced options - **Coverage is honest, not infinite.** Threads' public (cookie-free) search exposes a bounded sample per term — typically a few dozen posts. This actor widens it by unioning the relevance and recency views (`deepCoverage`, on by default), but there is **no deep cursor pagination on the public path**; `maxResultsPerQuery` caps what the union exposes. For broader sweeps, run several related queries. - **Monitor is the hands-off mode.** Set Mode = Monitor + an Apify Schedule. Dedup is code-based and persisted in a named store, so you never re-pull or re-pay for a post you already got. For very high-volume terms, an early run may surface a fresh slice each time as Threads rotates its public sample; it settles as the seen-set fills. - **Reply trees** return the top replies embedded in each post's page (depth-aware via reply-to-author). A post with thousands of replies returns its top discussion sample, not every reply. - **Contacts**: turn on `resolveLinktree` to follow Linktree / Beacons / Stan links for extra channels. Author rows are deduped — one per author per run. - **Use a residential proxy** (default) for reliability — Meta intermittently per-IP-gates social-bot fetches; rotation handles it. Datacenter works for tiny runs. - **Date window** (`dateFrom` / `dateTo`) filters the gathered set; it does not fetch posts older than Threads exposes. ### Legal & responsible use This actor collects **only public** Threads data available without logging in, via Meta's public social-bot rendering. It does not bypass authentication or access private/age-gated content. You are responsible for using the output in compliance with [Threads'/Meta's Terms](https://help.instagram.com/769983657850450), the [Apify Terms of Service](https://apify.com/terms-of-service), and applicable data-protection law (GDPR/CCPA) — especially for the contact-extraction feature, where you must have a lawful basis for processing personal data. No personal data is stored by the actor beyond the dataset it returns to you. ### FAQ & support **Why can't I get thousands of posts for one keyword?** Threads' public search has no cursor pagination without logging in. We widen coverage by unioning the relevance + recency views (a few dozen posts/term) and let you run many queries. We deliberately stay cookie-free for reliability rather than chase a login-gated pagination path. **How is this different from the generalist Threads scrapers?** This one is built for *search & monitoring*: multi-view coverage per term, a dedup-aware scheduled monitor, and reply + contact enrichment **on search results** — none of which the keyword-only incumbents bundle. **Does monitor mode re-charge me for the same post?** No. Dedup is persisted across runs in a named key-value store; you're only charged for posts you haven't seen. **Do I need a Threads/Meta account or API key?** No. No login, no cookies, no tokens. **Why did a query return nothing?** The term may have no public posts, or Meta gated that IP on the attempt — enable the residential proxy (default) and retry. **Support:** open an issue on the actor's **Issues** tab. Bugs and feature requests welcome. # Actor input Schema ## `mode` (type: `string`): Search and Hashtag pull current posts for your terms. Monitor re-runs your terms and returns only posts it hasn't seen before — point Apify Schedules at it for hands-off social listening. ## `searchQueries` (type: `array`): Keywords or phrases to search. Used by Search and Monitor modes. Each is gathered independently. ## `hashtags` (type: `array`): Tags without the #. Used by Hashtag and Monitor modes. ## `sort` (type: `string`): Top biases toward the relevance view; Recent biases toward the newest view. Monitor mode always uses Recent. ## `maxResultsPerQuery` (type: `integer`): Cap on unique posts gathered per term. Threads' cookie-free pages expose a bounded sample per term (typically a few dozen); this actor unions the relevance + recency views to widen it. There is no deep cursor pagination on the public path. ## `deepCoverage` (type: `boolean`): When on, fetch and union multiple Threads result views per term for the widest cookie-free coverage. Turn off for a single fast fetch per term. ## `includeReplies` (type: `boolean`): For each surfaced post, fetch its discussion/reply tree. Charged per reply. No incumbent ships replies on search results. ## `maxReplyDepth` (type: `integer`): How deep to follow nested reply chains. Only applies when Include reply trees is on. ## `maxRepliesPerNode` (type: `integer`): Cap replies kept per parent post (top N by like count). ## `resolveContacts` (type: `boolean`): For each unique author surfaced, resolve email + phone from their bio. Emits one deduped author row per author, charged once per author. Ideal for lead-gen. ## `resolveLinktree` (type: `boolean`): During contact resolution, follow Linktree / Beacons / Stan links to extract additional contact channels. Requires Resolve author bio contacts. ## `dateFrom` (type: `string`): Keep only posts on/after this date (YYYY-MM-DD). Narrows the gathered set — it does not fetch older posts beyond what Threads exposes. ## `dateTo` (type: `string`): Keep only posts on/before this date (YYYY-MM-DD). ## `maxItems` (type: `integer`): Hard cap on dataset rows for this run (posts + replies + author rows across all terms). Budget priority: posts first, then author contacts, then replies. ## `proxyConfiguration` (type: `object`): Residential proxy is recommended. Datacenter works for tiny runs but is more likely to hit Meta's intermittent IP gate. ## Actor input object example ```json { "mode": "search", "searchQueries": [ "threads api" ], "hashtags": [], "sort": "top", "maxResultsPerQuery": 50, "deepCoverage": true, "includeReplies": false, "maxReplyDepth": 2, "maxRepliesPerNode": 20, "resolveContacts": false, "resolveLinktree": false, "maxItems": 500, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `results` (type: `string`): All surfaced posts, replies, and resolved author contacts in one dataset. # 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 = { "searchQueries": [ "threads api" ], "hashtags": [] }; // Run the Actor and wait for it to finish const run = await client.actor("constructive_calm/threads-search-monitor").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 = { "searchQueries": ["threads api"], "hashtags": [], } # Run the Actor and wait for it to finish run = client.actor("constructive_calm/threads-search-monitor").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 '{ "searchQueries": [ "threads api" ], "hashtags": [] }' | apify call constructive_calm/threads-search-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=constructive_calm/threads-search-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Threads Search & Monitor - Keyword Tracking + Contacts", "description": "Search Threads by keyword/hashtag and monitor saved searches for new posts on a schedule. Optional reply trees + author bio contacts (email/phone). Cookie-free, no login.", "version": "0.1", "x-build-id": "lDjODOrVt2FaACSQJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/constructive_calm~threads-search-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-constructive_calm-threads-search-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/constructive_calm~threads-search-monitor/runs": { "post": { "operationId": "runs-sync-constructive_calm-threads-search-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/constructive_calm~threads-search-monitor/run-sync": { "post": { "operationId": "run-sync-constructive_calm-threads-search-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "search", "hashtag", "monitor" ], "type": "string", "description": "Search and Hashtag pull current posts for your terms. Monitor re-runs your terms and returns only posts it hasn't seen before — point Apify Schedules at it for hands-off social listening.", "default": "search" }, "searchQueries": { "title": "Search queries", "type": "array", "description": "Keywords or phrases to search. Used by Search and Monitor modes. Each is gathered independently.", "items": { "type": "string" } }, "hashtags": { "title": "Hashtags", "type": "array", "description": "Tags without the #. Used by Hashtag and Monitor modes.", "items": { "type": "string" } }, "sort": { "title": "Sort / bias", "enum": [ "top", "recent" ], "type": "string", "description": "Top biases toward the relevance view; Recent biases toward the newest view. Monitor mode always uses Recent.", "default": "top" }, "maxResultsPerQuery": { "title": "Max results per query", "minimum": 1, "maximum": 200, "type": "integer", "description": "Cap on unique posts gathered per term. Threads' cookie-free pages expose a bounded sample per term (typically a few dozen); this actor unions the relevance + recency views to widen it. There is no deep cursor pagination on the public path.", "default": 50 }, "deepCoverage": { "title": "Wide coverage (union of views)", "type": "boolean", "description": "When on, fetch and union multiple Threads result views per term for the widest cookie-free coverage. Turn off for a single fast fetch per term.", "default": true }, "includeReplies": { "title": "Include reply trees", "type": "boolean", "description": "For each surfaced post, fetch its discussion/reply tree. Charged per reply. No incumbent ships replies on search results.", "default": false }, "maxReplyDepth": { "title": "Max reply depth", "minimum": 0, "maximum": 10, "type": "integer", "description": "How deep to follow nested reply chains. Only applies when Include reply trees is on.", "default": 2 }, "maxRepliesPerNode": { "title": "Max replies per parent", "minimum": 1, "maximum": 200, "type": "integer", "description": "Cap replies kept per parent post (top N by like count).", "default": 20 }, "resolveContacts": { "title": "Resolve author bio contacts (premium)", "type": "boolean", "description": "For each unique author surfaced, resolve email + phone from their bio. Emits one deduped author row per author, charged once per author. Ideal for lead-gen.", "default": false }, "resolveLinktree": { "title": "Follow Linktree / aggregator links", "type": "boolean", "description": "During contact resolution, follow Linktree / Beacons / Stan links to extract additional contact channels. Requires Resolve author bio contacts.", "default": false }, "dateFrom": { "title": "Posted after (date)", "type": "string", "description": "Keep only posts on/after this date (YYYY-MM-DD). Narrows the gathered set — it does not fetch older posts beyond what Threads exposes." }, "dateTo": { "title": "Posted before (date)", "type": "string", "description": "Keep only posts on/before this date (YYYY-MM-DD)." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Hard cap on dataset rows for this run (posts + replies + author rows across all terms). Budget priority: posts first, then author contacts, then replies.", "default": 500 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Residential proxy is recommended. Datacenter works for tiny runs but is more likely to hit Meta's intermittent IP gate.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```