# Startupfast Scraper (`iskander/startupfast-scraper`) Actor - **URL**: https://apify.com/iskander/startupfast-scraper.md - **Developed by:** [Iskandar Souissi](https://apify.com/iskander) (community) - **Categories:** Lead generation, Automation - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 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 ### ๐Ÿš€ Startupfa.st Scraper Scrape product listings from [startupfa.st](https://www.startupfa.st/) โ€” a directory of SaaS tools, developer products, and indie projects. Select a category (or scrape all 38), optionally enrich each listing with full detail-page data including upvotes, pricing, tech stack, and social links. --- #### How to use it 1. [Register a free account](https://console.apify.com/sign-up) and start using this actor right away. 1. Go to the main page of this actor and configure your input. 1. Find all results in the Output tab and export in any format you need. #### โš™๏ธ How it works - **Input:** Choose a category slug (e.g. `ai`, `saas`, `devops`) or `all` to scrape every category. Toggle **Scrape Details** to fetch full product pages. - **List page:** Extracts name, description, website, logo, categories, and comment count for every product in the category. - **Detail page** *(scrapeDetails only)*: Fetches each product's page to add upvotes, cover image, pricing model, supported platforms, tech stack, launch date, and social links. - **Deduplication:** Products appearing in multiple categories are only scraped once. --- #### ๐Ÿงพ Example Input ```json { "category": "ai", "scrapeDetails": true } ```` *** #### ๐Ÿ“ค Example Output (single product, scrapeDetails enabled) ```json { "slug": "soniox", "name": "Soniox", "url": "https://www.startupfa.st/projects/soniox", "website": "https://soniox.com", "logo": "https://utfs.io/f/abc123", "description": "One speech AI API for realtime speech-to-text and audio understanding.", "categories": ["Artificial Intelligence", "APIs & Integrations"], "comments": 3, "cover_image": "https://utfs.io/f/xyz456", "upvotes": 42, "pricing": "freemium", "platforms": ["web"], "tech_stack": ["NEXTJS", "AI"], "launch_date": "Jun 18, 2025", "social_links": { "Twitter Link": "https://x.com/soniox_ai" } } ``` *** #### ๐Ÿ—‚๏ธ Input options | Field | Type | Description | |---|---|---| | `category` | string | Category slug or `all`. Defaults to `all`. | | `scrapeDetails` | boolean | Whether to fetch each product's detail page. Defaults to `false`. | *** #### ๐Ÿš€ Use Cases - SaaS market research and competitive analysis - Building curated directories or newsletters - Tracking new product launches by category - Lead generation for developer tools and B2B SaaS *** #### ๐Ÿง  Notes - Categories available: `api`, `ai`, `analytics`, `blockchain`, `cms`, `data-science`, `databases`, `design-tools`, `devops`, `developer-tools`, `ecommerce`, `edtech`, `finance-tech`, `gaming`, `graphics`, `greentech`, `hardware`, `healthtech`, `iot`, `machine-learning`, `marketing-tools`, `mobile-dev`, `nlp`, `open-source`, `platform`, `productivity`, `prototyping`, `robotics`, `saas`, `sales-tools`, `security`, `serverless`, `testing-qa`, `ui-ux`, `wearables`, `web-dev`, `ar-vr`. - `social_links` is a key-value map (e.g. `{"Twitter Link": "https://x.com/..."}`) โ€” only populated when the product has social links on its listing page. - Running with `scrapeDetails: false` is significantly faster and sufficient for bulk discovery. # Actor input Schema ## `category` (type: `string`): Which category to scrape. Choose "All categories" to scrape every category. ## `scrapeDetails` (type: `boolean`): When enabled, visits each product page to collect pricing, tech stack, platforms, launch date, cover image, and upvotes. Slower but more complete. ## Actor input object example ```json { "category": "blockchain", "scrapeDetails": false } ``` # Actor output Schema ## `results` (type: `string`): All scraped product listings # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("iskander/startupfast-scraper").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 = {} # Run the Actor and wait for it to finish run = client.actor("iskander/startupfast-scraper").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 '{}' | apify call iskander/startupfast-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=iskander/startupfast-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Startupfast Scraper", "version": "0.1", "x-build-id": "eR79xttqxpc1Mc8Zi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/iskander~startupfast-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-iskander-startupfast-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/iskander~startupfast-scraper/runs": { "post": { "operationId": "runs-sync-iskander-startupfast-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/iskander~startupfast-scraper/run-sync": { "post": { "operationId": "run-sync-iskander-startupfast-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "category" ], "properties": { "category": { "title": "Category", "enum": [ "all", "ai", "analytics", "api", "ar-vr", "blockchain", "cms", "data-science", "databases", "design-tools", "developer-tools", "devops", "ecommerce", "edtech", "finance-tech", "gaming", "graphics", "greentech", "hardware", "healthtech", "iot", "machine-learning", "marketing-tools", "mobile-dev", "nlp", "open-source", "platform", "productivity", "prototyping", "robotics", "saas", "sales-tools", "security", "serverless", "testing-qa", "ui-ux", "wearables", "web-dev" ], "type": "string", "description": "Which category to scrape. Choose \"All categories\" to scrape every category.", "default": "blockchain" }, "scrapeDetails": { "title": "Scrape full details", "type": "boolean", "description": "When enabled, visits each product page to collect pricing, tech stack, platforms, launch date, cover image, and upvotes. Slower but more complete.", "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 } } } } } } } } } } ```