# Pinterest Scraper - Pins by Keyword, Images & Stats (`santhej/pinterest-scraper-pro`) Actor Scrape Pinterest pins by search keyword: image URL, title, description, outbound link, pinner, board and engagement (repins, reactions). Fast, pay per pin, no login. - **URL**: https://apify.com/santhej/pinterest-scraper-pro.md - **Developed by:** [Santhej Kallada](https://apify.com/santhej) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% 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. 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 ## AI Rank Tracker Pro — Apify Actor Track brand visibility across **5 AI search platforms** (Google AI Overviews, ChatGPT, Claude, Gemini, Perplexity) in one run. Powered by DataForSEO. > **For the full user-facing docs**, see [.actor/README.md](.actor/README.md) — that's what shows up on the Apify Store listing. ### Repository layout ```` .actor/ ## Apify actor config (deployed) actor.json ## Actor metadata Dockerfile ## Build config input\_schema.json ## Input UI schema README.md ## Store listing README src/ ## TypeScript source main.ts ## Entry point types.ts ## Shared types config.ts ## Constants api/ ## DataForSEO clients (Mentions + Responses) detect/ ## Mention/citation/sentiment detection aggregate/ ## Top domains + visibility score + report builder billing/ ## Pay-per-event charging utils/ ## Helpers research/ ## Pre-build market research (not deployed) spec/ ## Design spec (not deployed) assets/ ## Logo (not deployed in actor; uploaded separately to Apify dashboard) ```` ### Local development ```bash ## Install deps npm install ## Set up environment cp .env.example .env ## Edit .env with DataForSEO + Apify + KIE credentials ## Build npm run build ## Run locally (uses INPUT.json in storage/key_value_stores/default/) npm run start ```` ### Deployment ```bash ## Log in to Apify (one time) apify login ## Push the actor apify push ``` The actor is deployed under [`santhej/ai-rank-tracker-pro`](https://apify.com/santhej/ai-rank-tracker-pro). ### Pricing model - `Actor Start` — $0.001 - `Platform Check` — $0.05 per (query × platform) - `Aggregated Report` — $0.25 (optional, opt-in via input) Minimum 3 queries per run. ### DataForSEO cost vs revenue (per typical run) | Scenario | DataForSEO cost | User pays | We receive (80%) | Margin | |---|---|---|---|---| | 3 queries × 5 platforms | ~$0.22 | $0.75 | $0.60 | 63% | | 5 queries × 5 platforms | ~$0.24 | $1.25 | $1.00 | 76% | | 10 queries × 5 platforms | ~$0.28 | $2.50 | $2.00 | 86% | ### License Proprietary. © 2026 Santhej Kallada. # Actor input Schema ## `queries` (type: `array`): Pinterest search terms, one per line. ## `maxPinsPerQuery` (type: `integer`): Maximum pins to collect per search term (1-1000). ## `proxyConfiguration` (type: `object`): Residential proxy is strongly recommended for Pinterest. ## Actor input object example ```json { "queries": [ "minimalist living room" ], "maxPinsPerQuery": 50, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `dataset` (type: `string`): All platform\_check records and the optional aggregated\_report row. ## `summary` (type: `string`): High-level run summary including overall visibility score, mention rate, and platform counts. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "minimalist living room" ] }; // Run the Actor and wait for it to finish const run = await client.actor("santhej/pinterest-scraper-pro").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "queries": ["minimalist living room"] } # Run the Actor and wait for it to finish run = client.actor("santhej/pinterest-scraper-pro").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 '{ "queries": [ "minimalist living room" ] }' | apify call santhej/pinterest-scraper-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=santhej/pinterest-scraper-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Pinterest Scraper - Pins by Keyword, Images & Stats", "description": "Scrape Pinterest pins by search keyword: image URL, title, description, outbound link, pinner, board and engagement (repins, reactions). Fast, pay per pin, no login.", "version": "0.0", "x-build-id": "zU0SGj2AdcmfuHlQs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/santhej~pinterest-scraper-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-santhej-pinterest-scraper-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/santhej~pinterest-scraper-pro/runs": { "post": { "operationId": "runs-sync-santhej-pinterest-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/santhej~pinterest-scraper-pro/run-sync": { "post": { "operationId": "run-sync-santhej-pinterest-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "queries": { "title": "Search queries", "type": "array", "description": "Pinterest search terms, one per line.", "items": { "type": "string" } }, "maxPinsPerQuery": { "title": "Max pins per query", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum pins to collect per search term (1-1000).", "default": 50 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Residential proxy is strongly recommended for Pinterest.", "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 } } } } } } } } } } ```