# Web Scraper API - Anti-Bot Profile Selection, BYO Proxy (`fenlo-services/stealth-scraper`) Actor Best-effort page fetcher that runs a quick anti-bot recon, auto-selects the matching engine request profile, and fetches the page through your own proxy. Returns HTML length, detected stack, and latency. - **URL**: https://apify.com/fenlo-services/stealth-scraper.md - **Developed by:** [Fenlo AI](https://apify.com/fenlo-services) (community) - **Categories:** Automation, Developer tools, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $500.00 / 1,000 page fetches This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Web Scraper API — Auto Anti-Bot Profile Selection (Bring Your Own Proxy) A best-effort page fetcher that first runs a quick anti-bot **recon**, then auto-selects the detection engine's matching request profile, and fetches the page through *your* proxy. There is no promise of access. If a site blocks the request, that blocked response is what you get back — this Actor makes a best-effort fetch and reports the outcome; it does not claim to get past any defense. ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `url` | string | — | The URL to fetch. | | `proxy` | string | — | Your own proxy URL, e.g. `http://user:pass@host:port`. Optional. | | `extract_text` | boolean | `false` | Also return best-effort plain text extracted from the HTML. | ### Output ```json { "html": "...", "html_length": 13407, "stack": "cloudflare", "latency_ms": 842, "text": "..." } ```` `html` is the full fetched page markup. `text` (best-effort plain text) is present only when `extract_text` is `true`. ### Bring your own proxy This Actor exposes a single proxy parameter by design. It has no proxy pool and no rotation — supply whichever proxy you already use. ### How it works 1. A lightweight probe detects the site's anti-bot stack. 2. The detection engine's recommended request profile for that stack is selected automatically. 3. A single browser fetch is made through your proxy; the Actor returns the fetched page HTML, its length, the detected stack, and the round-trip latency (plus optional plain text). For detection-only profiling across many URLs, see the companion **recon-meta** Actor. ### Build & deploy **This Actor is self-contained: the Docker build context is this Actor folder.** Apify confines the build context to the Actor's own directory, so a `COPY` cannot reach outside it. This Actor depends on the repo-local `fenlo_engine` package (source at `packages/engine` — outside this folder). Because Docker cannot `COPY` across folders, the engine is vendored here as a pre-built pip wheel (`fenlo_engine-*.whl`). Build the wheel into this folder first, then build the image with this folder as the context: ```bash ## From the repo root: build the engine wheel into a throwaway dist/ and copy it ## into this Actor dir. Do NOT use `-o actors/stealth-scraper`: `uv build` writes a ## `.gitignore` containing `*` into its output dir, which would re-ignore this ## Actor's .actorignore and break `apify push`. dist/ is already git-ignored. rm -f actors/stealth-scraper/fenlo_engine-*.whl uv build --wheel packages/engine -o dist cp dist/fenlo_engine-*.whl actors/stealth-scraper/ ## From inside this Actor dir (context = ".") cd actors/stealth-scraper docker build -t fenlo-stealth-scraper . ``` The `Dockerfile` (referenced from `.actor/actor.json`) then: 1. installs the vendored engine with `pip install fenlo_engine-*.whl`, and 2. installs this Actor's `requirements.txt` (the Apify SDK), so `import fenlo_engine` resolves inside the container. The base image is `apify/actor-python-playwright`, which ships the Chromium build this Actor uses for its browser fetch. **Trade-off:** the wheel is a vendored copy, so **rebuild it whenever `packages/engine` changes** (otherwise the Actor ships a stale engine). The wheel is git-ignored; a `.actorignore` re-includes it so `apify push` still uploads it. To publish on Apify: `cd actors/stealth-scraper && apify push` (rebuild the wheel first). See `docs/launch/PUBLISH.md`. # Actor input Schema ## `url` (type: `string`): The URL to fetch. ## `proxy` (type: `string`): Bring your own proxy, e.g. http://user:pass@host:port. Optional; the Actor has no proxy pool of its own. ## `extract_text` (type: `boolean`): Return best-effort plain text extracted from the fetched HTML. ## Actor input object example ```json { "url": "https://example.com", "extract_text": false } ``` # Actor output Schema ## `results` (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 = { "url": "https://example.com" }; // Run the Actor and wait for it to finish const run = await client.actor("fenlo-services/stealth-scraper").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 = { "url": "https://example.com" } # Run the Actor and wait for it to finish run = client.actor("fenlo-services/stealth-scraper").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 '{ "url": "https://example.com" }' | apify call fenlo-services/stealth-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fenlo-services/stealth-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Web Scraper API - Anti-Bot Profile Selection, BYO Proxy", "description": "Best-effort page fetcher that runs a quick anti-bot recon, auto-selects the matching engine request profile, and fetches the page through your own proxy. Returns HTML length, detected stack, and latency.", "version": "0.1", "x-build-id": "9Q3AGFxSXNuh8CgPK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fenlo-services~stealth-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fenlo-services-stealth-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fenlo-services~stealth-scraper/runs": { "post": { "operationId": "runs-sync-fenlo-services-stealth-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fenlo-services~stealth-scraper/run-sync": { "post": { "operationId": "run-sync-fenlo-services-stealth-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "url" ], "properties": { "url": { "title": "Target URL", "type": "string", "description": "The URL to fetch." }, "proxy": { "title": "Your proxy URL", "type": "string", "description": "Bring your own proxy, e.g. http://user:pass@host:port. Optional; the Actor has no proxy pool of its own." }, "extract_text": { "title": "Also return plain text", "type": "boolean", "description": "Return best-effort plain text extracted from the fetched HTML.", "default": false } } }, "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 } } } } } } } } } } ```