# Instagram Creator & Influencer Marketing Intel (`seibs.co/instagram-creator-intel`) Actor Influencer analytics from public Instagram profiles (+ optional TikTok/YouTube): follower count, engagement rate, avg likes/comments, posting cadence, audience-quality / fake-follower heuristics, and top content. The Modash/HypeAuditor layer without Meta App Review. For brands, DTC, and agencies. - **URL**: https://apify.com/seibs.co/instagram-creator-intel.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** Business, Marketing, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 creator records 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 ## Instagram Creator & Influencer Marketing Intel > **TL;DR for brands, DTC, and influencer-marketing agencies:** Pull a creator's **public Instagram** profile and recent posts and get the influencer-analytics layer that **Modash / HypeAuditor ($299+/mo) and Upfluence ($478+/mo)** charge for - **engagement rate, avg likes/comments, posting cadence, top content, category, and an audience-quality / fake-follower estimate** - with no Meta App Review. Optionally cross-reference the same creator on **TikTok and YouTube** for a multi-platform reach view. The official path (Instagram Graph API) is a 4-6 week App-Review + Business-Verification gauntlet most never clear, and only works on accounts you manage; this needs no application. Logged-out public profiles only, no login, no account creation, PII minimized to the public creator/business identity. ### Run it in 30 seconds ```python ## Via the Apify Python SDK from apify_client import ApifyClient client = ApifyClient("") run = client.actor("seibs.co/instagram-creator-intel").call(run_input={ "mode": "audience_quality", "creators": ["@natgeo", "nasa"], "platforms": ["instagram"] }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ```` Or via curl: ```bash curl -X POST "https://api.apify.com/v2/acts/seibs.co~instagram-creator-intel/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{"mode": "creator_profile", "creators": ["natgeo"], "platforms": ["instagram"]}' ``` Or click "Try for free" on this page if you prefer the no-code UI. ### What you get Each run produces: - A clean dataset, filterable in the Apify console and downloadable as CSV or JSON - An `access_notes` record up top documenting each surface's access method, anti-bot tier, escalation telemetry, and the legal posture - A sample-output preview at [`.actor/sample-output.json`](./.actor/sample-output.json) ### What does Creator Intel do? It looks up each creator's **public profile** and recent posts, then normalizes everything into one schema: `platform`, `username`, `canonical_handle` (the cross-platform join key), `full_name`, `biography`, `category`, `is_verified`, `account_type`, `followers`, `following`, `posts_count`, `follower_tier` (nano / micro / mid / macro / mega), and a `recent_posts` stream with per-post like/comment counts. Then it runs the **value layer** - the part influencer platforms gate behind a subscription: - **Engagement analysis** - engagement rate, avg/median likes & comments, like:comment ratio, **posting cadence per week**, format mix (image/video/carousel), **top content**, a **follower-tier benchmark comparison** (above / in-band / below the typical engagement for that follower size), and inferred **category**. - **Audience quality** - a **fake-follower / audience-credibility estimate** computed from public signals only: engagement rate vs the follower-tier band, like:comment ratio, following ratio, and engagement uniformity, scored into a 0-100 credibility band with explained flags. This is the premium authenticity signal Modash/HypeAuditor sell. It is clearly labeled a **heuristic estimate** - a prioritization aid for manual vetting, never a definitive verdict. - **Cross-platform + roster** - group a creator across Instagram/TikTok/YouTube into a **multi-platform reach rollup**, and rank a set of creators in a **roster-comparison** table (best engagement, best credibility, category mix). ### Modes | Mode | What it returns | |---|---| | `creator_profile` (default) | Each creator's public profile + recent posts + the engagement-analysis layer. | | `audience_quality` | `creator_profile` plus the fake-follower / audience-credibility estimate (the premium signal). | | `roster_compare` | `creator_profile` for a set of creators plus a cross-creator ranking table for influencer-roster selection. | ### Platform coverage + access notes Instagram is the primary surface; TikTok and YouTube are optional cross-reference footprints. Coverage is honestly described per surface: | Platform | Surface | Access | Notes | |---|---|---|---| | **instagram** | Public profile (`web_profile_info`) | http-first, browser fallback | The logged-out JSON endpoint returns the profile + the ~12 most-recent posts with like/comment counts, gated by an `X-IG-App-ID` header + a `datr` cookie a real page load mints. curl\_cffi clears the TLS fingerprint; the browser tier loads the public profile page and captures the page's *own* `web_profile_info` XHR (no forged token, no login). | | **tiktok** | Public profile (`__UNIVERSAL_DATA_FOR_REHYDRATION__`) | http-first, browser fallback | The profile page embeds follower / heart / video counts; used as a cross-platform reach reference (per-post engagement is approximated from total likes รท video count). | | **youtube** | Public channel (`ytInitialData`) | http-first, browser fallback | The channel page embeds subscriber + video counts; cross-platform reach reference. | Where a logged-out request is blocked, the account is private, or the shape can't be parsed, the platform fails soft with a documented `platform_pending` / `fetch_error` note (the run still finishes SUCCEEDED) rather than fabricating data. ### Anti-bot escalation (residential + browser) Each profile request runs an automatic escalation ladder: 1. **httpx** over the DATACENTER proxy - cheapest, used first. 2. **curl\_cffi** with real Chrome TLS impersonation over the RESIDENTIAL proxy - defeats JA3/TLS-fingerprint WAFs (Instagram's edge). 3. **Playwright** (patchright stealth) over RESIDENTIAL - loads the public profile page and captures/replays its own `web_profile_info` XHR (carrying the live cookies). This is what makes Instagram's token-locked endpoint return data. 4. **Fail-soft** - documented note, run stays SUCCEEDED. Set `use_browser_fallback=false` to use plain httpx only (Instagram then returns a `platform_pending` note). For the most reliable Instagram clearance, point the browser tier at a warm anti-detect browser via `browser_cdp_url` (or the `BROWSER_CDP_URL` env var); otherwise run on the `apify/actor-python-playwright` image so a headless Chromium is available. ### Monitor mode (roster tracking) Run this actor on an Apify **Schedule** and it switches to monitor mode: it diffs this run's creators against the last scheduled run and emits a `monitor_digest` of **follower / engagement-rate movement** and **newly-added creators**, optionally posting the digest to a Slack-compatible `monitor_webhook_url`. Charges one `scheduled_delta_run` per scheduled run. This is the "track my influencer roster over time" use case. ### Responsible use / data scope Logged-out **public profiles** only, no account creation, no login, no paid API token, no private/credentialed data. We minimize PII: the identity we keep is the **public creator/business profile** (handle, display name, bio, public counts, public post engagement) - we never resolve a private individual's contact details. Meta v. Bright Data (2024) held that logged-off scraping of public Meta data is not barred by its terms. Use creator data responsibly, respect each platform's terms and your local regulations, and treat the audience-quality estimate as a vetting aid, not a verdict. ### AI / RAG / Agent The `overview` dataset view is a narrow, token-efficient slice for LLM tool responses. A paired **MCP server** (`mcp-instagram-creator-intel`) exposes these as agent tools (`get_creator_profile`, `analyze_engagement`, `check_audience_quality`, `compare_creators`, `cross_platform_lookup`) and is x402 (USDC on Base) + Skyfire ready for token-less agentic payments. ### Features - The Modash / HypeAuditor analytics layer (engagement rate, fake-follower estimate) without Meta App Review - Engagement rate, avg/median likes & comments, posting cadence, format mix, top content - Audience-quality / fake-follower heuristic estimate with explained flags (no LLM key required) - Follower-tier benchmark comparison + category inference - Multi-platform reach rollups (Instagram + TikTok + YouTube) and roster-comparison ranking - Roster-tracking monitor mode with Slack webhook - Anti-bot escalation (curl\_cffi + browser XHR capture) with fail-soft notes - Pay-per-event pricing that undercuts the $299+/mo influencer-platform stack ### Use cases - **Influencer vetting** - is this creator's engagement real, or are the followers bought? Check before you pay for a campaign. - **Roster selection** - rank a shortlist of creators by engagement rate and audience credibility. - **Creator discovery QA** - validate a list of handles' follower size, niche, and engagement in bulk. - **Multi-platform reach** - one creator's combined Instagram + TikTok + YouTube footprint. - **Roster monitoring** - track follower / engagement movement across your influencer roster over time. ### Pricing (Pay Per Event) | Event | Price | When | |---|---|---| | `creator_record` | $0.006 | Per normalized public creator profile | | `engagement_analysis` | $0.010 | Per creator's engagement layer (rate, cadence, top content, benchmark) | | `audience_quality_flag` | $0.015 | Per fake-follower / credibility estimate | | `scheduled_delta_run` | $0.050 | Per scheduled monitor-mode delta digest | A run that returns nothing costs nothing. The free Apify plan covers exploration runs on your $5 platform credit. ### Related actors Part of the Seibs.co intelligence portfolio. Distinct from `ad-library-intel` (paid **ads** across Meta/Google/TikTok) and `tiktok-shop-creator-intel` (TikTok **shop/commerce** creators) - this is **organic influencer-marketing analytics**. Pairs well with `ad-library-intel` (a creator's organic reach + a brand's paid ads) and the MCP twin `mcp-instagram-creator-intel`. # Actor input Schema ## `mode` (type: `string`): creator\_profile = pull each creator's public profile + recent posts and compute the engagement-analysis layer. audience\_quality = creator\_profile plus the fake-follower / audience-credibility estimate (the premium signal). roster\_compare = creator\_profile for a set of creators plus a cross-creator ranking table for roster selection. ## `creators` (type: `array`): Instagram @handles, bare usernames, or profile URLs to analyze, e.g. \['@natgeo', 'nike', 'https://instagram.com/glossier']. When TikTok / YouTube are included, the same handle is looked up on each platform for a multi-platform view. Hard cap of 50. ## `platforms` (type: `array`): Which public creator surfaces to query: instagram (primary), tiktok (cross-reference footprint), youtube (cross-reference footprint). Aliases like 'ig', 'tt', 'yt' are accepted. Leave empty for Instagram only. ## `include_cross_platform` (type: `boolean`): Shortcut to look the same handle up on Instagram + TikTok + YouTube and emit a multi-platform reach rollup (overrides the platforms list). ## `include_engagement_analysis` (type: `boolean`): Compute engagement rate, avg/median likes & comments, like:comment ratio, posting cadence, format mix, top content, follower-tier benchmark, and inferred category. Adds an engagement\_analysis PPE charge per creator. This is the core analytics layer. ## `include_audience_quality` (type: `boolean`): Compute the fake-follower / audience-credibility estimate (credibility score + band + flags) from public signals. Adds an audience\_quality\_flag PPE charge per creator. Forced on in audience\_quality mode. This is the premium authenticity signal Modash / HypeAuditor gate behind subscriptions. ## `max_posts` (type: `integer`): How many recent posts to factor into the engagement math. Instagram exposes ~12 logged-out; default 12. ## `monitor_webhook_url` (type: `string`): When this actor runs under an Apify Schedule (monitor mode), post the change digest (follower / engagement movement, newly-added creators) to this Slack-compatible webhook URL. ## `contact_email` (type: `string`): Optional. Sent as an X-Contact header so a platform can reach you - a good-citizen signal. Not a credential and never used to log in. ## `use_apify_proxy` (type: `boolean`): Route requests through Apify Proxy. DATACENTER handles the first (httpx) pass; a RESIDENTIAL tier is provisioned for the anti-bot escalation legs (Instagram fingerprints datacenter IPs). ## `use_browser_fallback` (type: `boolean`): When a surface serves an anti-bot / login challenge (Instagram's profile JSON is token-locked), automatically escalate: switch to the RESIDENTIAL proxy and retry with curl\_cffi Chrome TLS impersonation, then a headless browser that loads the public profile page and captures the page's own web\_profile\_info XHR. Turn off to use plain httpx only (Instagram then returns a documented platform\_pending note). ## `browser_cdp_url` (type: `string`): Optional. CDP/WebSocket endpoint of an already-running, anti-detect (UC-mode / real Chrome) browser. When set, the browser tier connects to it (inheriting its session + fingerprint) so it clears Instagram's edge reliably. Without it a plain headless Chromium is launched (works on the apify/actor-python-playwright image; weaker against managed challenges). Can also be set as the BROWSER\_CDP\_URL env var. ## `apify_proxy_groups` (type: `array`): Override the auto-selected proxy group. Leave empty to let the actor pick DATACENTER for the first pass and RESIDENTIAL for escalation. ## `concurrency` (type: `integer`): Parallel profile fetches. The surfaces are rate-sensitive; default 4. ## Actor input object example ```json { "mode": "creator_profile", "creators": [ "natgeo", "nasa" ], "platforms": [ "instagram" ], "include_cross_platform": false, "include_engagement_analysis": true, "include_audience_quality": false, "max_posts": 12, "monitor_webhook_url": "", "contact_email": "", "use_apify_proxy": true, "use_browser_fallback": true, "browser_cdp_url": "", "apify_proxy_groups": [], "concurrency": 4 } ``` # Actor output Schema ## `datasetItems` (type: `string`): Narrow, token-efficient slice of every record. Consumer: LLM agents (Claude, GPT, LangChain tools), MCP hosts, dashboards. Fields: platform, handle, followers, engagement rate, follower tier, credibility band, category, verified. ## `datasetItemsCreators` (type: `string`): All fields for every creator: profile, recent posts, full engagement analysis, audience-quality estimate. Consumer: humans browsing the dataset, RAG ingest, full backups. Larger payload - not recommended as a direct LLM tool response. ## `datasetItemsRoster` (type: `string`): Cross-creator ranking tables and multi-platform reach rollups. Consumer: influencer-roster selection, agency reporting. ## `datasetItemsMcp` (type: `string`): First 50 overview records as a clean JSON array. Wrap on the agent side in an MCP tool-call response envelope, e.g. `{ "ok": true, "data": , "meta": { "actor": "instagram-creator-intel", "count": , "view": "overview" } }`. Consumer: MCP servers, Claude Desktop, Cursor, OpenAI Assistants tool calls. ## `datasetItemsCsv` (type: `string`): Spreadsheet-friendly export of the overview view. Consumer: humans, marketing-ops teams, Excel / Google Sheets users. # 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 = { "mode": "creator_profile", "creators": [ "natgeo", "nasa" ], "platforms": [ "instagram" ], "max_posts": 12 }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/instagram-creator-intel").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 = { "mode": "creator_profile", "creators": [ "natgeo", "nasa", ], "platforms": ["instagram"], "max_posts": 12, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/instagram-creator-intel").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 '{ "mode": "creator_profile", "creators": [ "natgeo", "nasa" ], "platforms": [ "instagram" ], "max_posts": 12 }' | apify call seibs.co/instagram-creator-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/instagram-creator-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Creator & Influencer Marketing Intel", "description": "Influencer analytics from public Instagram profiles (+ optional TikTok/YouTube): follower count, engagement rate, avg likes/comments, posting cadence, audience-quality / fake-follower heuristics, and top content. The Modash/HypeAuditor layer without Meta App Review. For brands, DTC, and agencies.", "version": "0.1", "x-build-id": "pgYBuTGq3SZx2qRFs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~instagram-creator-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-instagram-creator-intel", "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/seibs.co~instagram-creator-intel/runs": { "post": { "operationId": "runs-sync-seibs.co-instagram-creator-intel", "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/seibs.co~instagram-creator-intel/run-sync": { "post": { "operationId": "run-sync-seibs.co-instagram-creator-intel", "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": [ "creator_profile", "audience_quality", "roster_compare" ], "type": "string", "description": "creator_profile = pull each creator's public profile + recent posts and compute the engagement-analysis layer. audience_quality = creator_profile plus the fake-follower / audience-credibility estimate (the premium signal). roster_compare = creator_profile for a set of creators plus a cross-creator ranking table for roster selection.", "default": "creator_profile" }, "creators": { "title": "Creators (@handles, usernames, or profile URLs)", "maxItems": 50, "type": "array", "description": "Instagram @handles, bare usernames, or profile URLs to analyze, e.g. ['@natgeo', 'nike', 'https://instagram.com/glossier']. When TikTok / YouTube are included, the same handle is looked up on each platform for a multi-platform view. Hard cap of 50.", "default": [], "items": { "type": "string" } }, "platforms": { "title": "Platforms", "maxItems": 3, "uniqueItems": true, "type": "array", "description": "Which public creator surfaces to query: instagram (primary), tiktok (cross-reference footprint), youtube (cross-reference footprint). Aliases like 'ig', 'tt', 'yt' are accepted. Leave empty for Instagram only.", "items": { "type": "string", "enum": [ "instagram", "tiktok", "youtube" ] }, "default": [ "instagram" ] }, "include_cross_platform": { "title": "Cross-platform view (add TikTok + YouTube)", "type": "boolean", "description": "Shortcut to look the same handle up on Instagram + TikTok + YouTube and emit a multi-platform reach rollup (overrides the platforms list).", "default": false }, "include_engagement_analysis": { "title": "Engagement analysis", "type": "boolean", "description": "Compute engagement rate, avg/median likes & comments, like:comment ratio, posting cadence, format mix, top content, follower-tier benchmark, and inferred category. Adds an engagement_analysis PPE charge per creator. This is the core analytics layer.", "default": true }, "include_audience_quality": { "title": "Audience quality (fake-follower estimate)", "type": "boolean", "description": "Compute the fake-follower / audience-credibility estimate (credibility score + band + flags) from public signals. Adds an audience_quality_flag PPE charge per creator. Forced on in audience_quality mode. This is the premium authenticity signal Modash / HypeAuditor gate behind subscriptions.", "default": false }, "max_posts": { "title": "Max recent posts to analyze", "minimum": 1, "maximum": 30, "type": "integer", "description": "How many recent posts to factor into the engagement math. Instagram exposes ~12 logged-out; default 12.", "default": 12 }, "monitor_webhook_url": { "title": "Monitor webhook URL (Slack / email, optional)", "type": "string", "description": "When this actor runs under an Apify Schedule (monitor mode), post the change digest (follower / engagement movement, newly-added creators) to this Slack-compatible webhook URL.", "default": "" }, "contact_email": { "title": "Contact email (polite-scraping signal, optional)", "type": "string", "description": "Optional. Sent as an X-Contact header so a platform can reach you - a good-citizen signal. Not a credential and never used to log in.", "default": "" }, "use_apify_proxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route requests through Apify Proxy. DATACENTER handles the first (httpx) pass; a RESIDENTIAL tier is provisioned for the anti-bot escalation legs (Instagram fingerprints datacenter IPs).", "default": true }, "use_browser_fallback": { "title": "Anti-bot escalation (curl_cffi + browser)", "type": "boolean", "description": "When a surface serves an anti-bot / login challenge (Instagram's profile JSON is token-locked), automatically escalate: switch to the RESIDENTIAL proxy and retry with curl_cffi Chrome TLS impersonation, then a headless browser that loads the public profile page and captures the page's own web_profile_info XHR. Turn off to use plain httpx only (Instagram then returns a documented platform_pending note).", "default": true }, "browser_cdp_url": { "title": "Warm browser CDP endpoint (for token-locked Instagram)", "type": "string", "description": "Optional. CDP/WebSocket endpoint of an already-running, anti-detect (UC-mode / real Chrome) browser. When set, the browser tier connects to it (inheriting its session + fingerprint) so it clears Instagram's edge reliably. Without it a plain headless Chromium is launched (works on the apify/actor-python-playwright image; weaker against managed challenges). Can also be set as the BROWSER_CDP_URL env var.", "default": "" }, "apify_proxy_groups": { "title": "Proxy groups (optional override)", "type": "array", "description": "Override the auto-selected proxy group. Leave empty to let the actor pick DATACENTER for the first pass and RESIDENTIAL for escalation.", "default": [], "items": { "type": "string" } }, "concurrency": { "title": "Max concurrent requests", "minimum": 1, "maximum": 8, "type": "integer", "description": "Parallel profile fetches. The surfaces are rate-sensitive; default 4.", "default": 4 } } }, "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 } } } } } } } } } } ```