# Instacart Email Scraper (`scraper-mind/instacart-email-scraper`) Actor Instacart Email Scraper – Effortlessly extract Instacart email addresses! 🔍 Search by keywords, location & custom domains to find targeted contacts. Supports Instacart listings ✅ Proxy support for smooth scraping. 📊 Download in JSON, CSV, Excel. Perfect for lead gen & outreach! - **URL**: https://apify.com/scraper-mind/instacart-email-scraper.md - **Developed by:** [Scraper Mind](https://apify.com/scraper-mind) (community) - **Categories:** Lead generation, Automation, Other - **Stats:** 7 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ### Instacart Email Scraper - Fast, Accurate & Affordable ⚡️👌 Unlock the power of **Instacart email scraping** with the **Instacart Email Scraper**! Fast, Accurate & Affordable ⚡️👌, this tool is designed to help you collect **Instacart emails** based on specified keywords, ideal for marketers, researchers, and businesses looking to expand their reach. --- #### 🔍 Key Features - **Keyword-Based Search:** Enter keywords like "john", "marketing", and more to find specific **Instacart email** addresses. - **Location Filtering:** Refine results by specifying the location. - **Platform Selection:** Specifically scrapes **Instacart** listings. - **Custom Email Domains:** Customize the email domains to be included in the search (default is @gmail.com). - **Proxy Support:** Use proxies to avoid rate-limiting issues and scrape seamlessly. --- #### 📚 Input Parameters ```json { "keywords": ["john", "marketing"], "location": "California", "platform": "Instacart", "customDomains": ["@gmail.com"], "proxyConfiguration": { "useApifyProxy": true } } ```` The **Instacart Email Scraper** uses the following input parameters for customization: - **keywords:** - A list of keywords to search for (e.g., `["john", "marketing"]`). - **location:** - Filter search results by location (optional). - **platform:** - Scrapes from **Instacart** (this is the only available option). - **customDomains:** - A list of custom email domains to filter the results (e.g., `@gmail.com`). - **proxyConfiguration:** - Optional setting for configuring proxy usage. *** #### 📈 Output Structure The output data is structured as follows: - **keyword:** The search keyword used. - **title:** The name of the app or listing associated with the email address. - **description:** A description containing the extracted email address. - **url:** The link to the Instacart page where the email was found. - **email:** The extracted email address. ##### Example Output JSON ```json [ { "keyword": "john", "title": "John's Grocery Shop", "description": "Contact us at johnsgrocery@gmail.com", "url": "https://www.instacart.com/store/johns-grocery-shop", "email": "johnsgrocery@gmail.com" } ] ``` *** #### 🛠️ How to Use 1. **Input Keywords and Email Domains:** - Enter the desired keywords (e.g., `["john", "marketing"]`) and custom email domains. 2. **Run the Actor:** - Click on **Run** to start the email scraping process from **Instacart**. 3. **Enable Proxies (Optional):** - If you need to scrape at a high volume, set up proxies to avoid rate-limiting issues. 4. **Download & Use the Data:** - After scraping, you can download the results in formats like **JSON**, **CSV**, or **Excel** for outreach, marketing, or further analysis. *** #### 👩‍🎓 Best Use Cases - **Lead Generation:** Build a list of **Instacart emails** for marketing and outreach. - **Market Research:** Gather contact details of businesses or service providers using **Instacart**. - **Data Aggregation:** Integrate **Instacart email** data into your CRM or email marketing tool. - **Partnership Development:** Identify contacts for potential collaborations and partnerships in the grocery delivery industry. *** #### 💬 Support & Feedback Need help with the **Instacart Email Scraper** or have feedback to improve it? We would love to hear from you! Contact us through our support channels for any questions or suggestions. # Actor input Schema ## `keywords` (type: `array`): A list of keywords to search for. ## `location` (type: `string`): Location to filter search results. ## `platform` (type: `string`): Select platform. ## `customDomains` (type: `array`): List of custom email domains ## `proxyConfiguration` (type: `object`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "burger", "chicken" ], "location": "", "platform": "Instacart", "customDomains": [ "@gmail.com" ] } ``` # 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 = { "keywords": [ "burger", "chicken" ], "location": "", "customDomains": [ "@gmail.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraper-mind/instacart-email-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 = { "keywords": [ "burger", "chicken", ], "location": "", "customDomains": ["@gmail.com"], } # Run the Actor and wait for it to finish run = client.actor("scraper-mind/instacart-email-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 '{ "keywords": [ "burger", "chicken" ], "location": "", "customDomains": [ "@gmail.com" ] }' | apify call scraper-mind/instacart-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper-mind/instacart-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instacart Email Scraper", "description": "Instacart Email Scraper – Effortlessly extract Instacart email addresses! 🔍 Search by keywords, location & custom domains to find targeted contacts. Supports Instacart listings ✅ Proxy support for smooth scraping. 📊 Download in JSON, CSV, Excel. Perfect for lead gen & outreach!", "version": "0.0", "x-build-id": "HeTNKyndEngopSc9z" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper-mind~instacart-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper-mind-instacart-email-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraper-mind~instacart-email-scraper/runs": { "post": { "operationId": "runs-sync-scraper-mind-instacart-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraper-mind~instacart-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraper-mind-instacart-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "A list of keywords to search for.", "default": [ "burger", "chicken" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "platform": { "title": "Platform", "enum": [ "Instacart" ], "type": "string", "description": "Select platform.", "default": "Instacart" }, "customDomains": { "title": "Custom Email Domains", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com" ], "items": { "type": "string" } }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Configure proxies for this Actor." } } }, "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 } } } } } } } } } } ```