# Figma Email Scraper Fast Advanced And Cheapest (`solid-scraper/figma-email-scraper-fast-advanced-and-cheapest`) Actor 🚀 Figma Email Scraper Fast Advanced & Cheapest extracts verified emails from design communities—quickly and accurately. Perfect for agencies, B2B sales, and marketers to build targeted lists fast. ⚡🔎 Affordable. - **URL**: https://apify.com/solid-scraper/figma-email-scraper-fast-advanced-and-cheapest.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### Figma Email Scraper - Fast, Advanced and Cheapest 📬 **Figma Email Scraper - Fast, Advanced and Cheapest** helps you extract email addresses from Figma based on the keywords and email-domain filters you choose. If you’re looking for a **Figma email scraper tool**, a **Figma email finder**, or a **Figma contact email extractor**, this actor automates the tedious “find leads → copy emails → organize data” workflow—so you can build a **Figma to email list** quickly and at scale. Whether you’re a marketer, researcher, recruiter, or data analyst, this tool turns publicly available contact clues into usable results, saving you hours of manual work. --- ### Why choose Figma Email Scraper - Fast, Advanced and Cheapest? | Feature | Benefit | | --- | --- | | ✅ **Keyword-driven email extraction from Figma** | Extracts email addresses using the keywords you provide and pushes results immediately to the dataset | | ✅ **Custom email-domain filtering** | Collects emails only from domains you specify (e.g. `@gmail.com`) to reduce noise for your outreach | | ✅ **Reliability with pagination + fallbacks** | Includes logic to keep going across pages and handle pages with empty/limited results | | ✅ **Deduplication of emails** | Avoids returning the same email multiple times during a run | | ✅ **Real-time structured dataset output** | Produces a clean row format with keyword, title, description, url, and email for easy exporting | | ✅ **Scales with limits you control** | You set `maxEmails` (up to 10000) to balance coverage, time, and cost | --- ### Key features - 🔎 **Figma email extraction with keyword focus**: Use `keywords` to target the kinds of contacts you want and scrape matching emails - 🧩 **Email-domain controls for cleaner leads**: Filter results with `customDomains` so your **Figma email database** stays relevant - 🛡️ **Resilient scraping flow**: Includes handling for empty/blocked pages and continues intelligently across the run - 🧠 **Unique email collection**: Keeps a `seen_emails` set so the same email won’t be pushed twice in one run - 💾 **Incremental saving to dataset**: Each found lead row is pushed right away using `Actor.push_data` - 🔄 **Resume support**: Persists progress so you can continue without losing already-found emails - 📊 **Controlled run scope**: Use `maxEmails` to stop once you hit your target (helpful for a **cheap Figma email scraper** approach) --- ### Input Provide input via an `input.json` file. Example structure: ```json { "keywords": ["manager", "founder"], "location": "", "customDomains": ["@gmail.com", "@yahoo.com"], "maxEmails": 20 } ```` #### Input Fields | Key | Required | Description | | --- | --- | --- | | `keywords` | ✅ Yes | A list of keywords or queries to search for. These guide the email extraction you’ll get from Figma-based public sources. | | `location` | ❌ No | Location to filter search results. Leave it empty for broader coverage. | | `customDomains` | ❌ No | List of custom email domains (for example `@gmail.com`, `@yahoo.com`). Emails are extracted only when they match these domains. | | `maxEmails` | ❌ No | Maximum number of emails to collect. The scraper stops once this limit is reached. Higher limits can take longer and don’t guarantee you’ll reach the exact number. (Minimum: `1`, Maximum: `10000`, Default: `20`.) | *** ### Output The actor saves each lead row as a JSON dataset record (pushed via `Actor.push_data`). Each row represents one extracted email tied to a keyword. Example output row: ```json [ { "network": "Figma.com", "keyword": "manager", "title": "No title", "description": "No data", "url": "No URL", "email": "example@gmail.com" } ] ``` #### Output Fields | Field | Type | Description | | --- | --- | | `network` | string | Source label used in the row (set to `Figma.com`) | | `keyword` | string | The keyword from your `keywords` input that led to this result | | `title` | string | Title text extracted from the result item (falls back to `No title`) | | `description` | string | Human-readable extracted description text (falls back to `No data`) | | `url` | string | URL extracted from the result item (falls back to `No URL`) | | `email` | string | The extracted email address | | `error_message` | string | ❌ Not present in pushed output rows from the provided source code (no explicit error field is pushed) | After the run, you can export the dataset (JSON/CSV) from Apify Console to use it in CRMs, spreadsheets, or analysis pipelines. *** ### How to use Figma Email Scraper - Fast, Advanced and Cheapest (via Apify Console) 1. **Open Apify Console**: Log in at https://console.apify.com and go to the Actors section. 2. **Find the actor**: Search for **Figma Email Scraper - Fast, Advanced and Cheapest** and open the actor page. 3. **Go to the INPUT tab**: Use the built-in input form (or paste an `input.json`) to set: - `keywords` (required) - `location` (optional) - `customDomains` (optional, recommended for cleaner results) - `maxEmails` (optional, Default `20`) 4. **Choose your run options (timeout)**: If you need more coverage, you can extend the timeout in **Run Options** (default is 3600 seconds / 1 hour). 5. **Start the run**: Click **Run**. Watch the logs as the actor progresses and pushes results incrementally to the dataset. 6. **Monitor progress**: The actor tracks found emails and supports resuming from saved progress if the run is interrupted. 7. **Open the dataset in OUTPUT**: After completion, open the output dataset titled **Figma Emails Dataset** and preview the scraped leads. 8. **Export your results**: Export as JSON/CSV and feed into your lead generation workflow, like building a **Figma creator email scraper** lead list. No coding required—get accurate results in minutes with this **Figma email scraper tool**. *** ### Advanced features & SEO optimization - ⚡ **Engineered for Figma email scraping at speed**: Built to quickly push each discovered lead row to your dataset as it’s found - 🎯 **Domain-targeted accuracy**: Uses your `customDomains` to focus results on email types you want (ideal for a **Figma email finder** that doesn’t waste time) - 🔄 **Resilience and fallbacks**: Includes logic to handle empty or limited result pages so runs can complete more reliably - 🧾 **Input normalization & resume**: Supports resuming using saved progress state, and prevents duplicates using a `seen_emails` set - 🛡️ **Designed for safe, public-source lead collection**: Extracts emails from publicly available sources and applies practical stop conditions via `maxEmails` *** ### Best use cases - 📈 **B2B lead generation from Figma profiles**: Build a targeted **Figma to email list** using job-title keywords like `manager` or `founder` - 🎯 **Research-backed outreach lists**: Generate a **Figma email database** filtered by domains (e.g., `@gmail.com`) to match your contact strategy - 🧠 **Email enrichment for marketers**: Add contact emails to existing prospect data when you’re scraping leads from Figma-related public profiles - 🛠️ **CRM pipeline automation**: Pull structured rows (keyword, title, description, url, email) and import into tools that manage outreach sequences - 🧾 **Bulk email extraction from Figma files (publicly referenced)**: Increase coverage using multiple keywords and broader domain lists for a **fast Figma email scraping** workflow - 🧑‍💼 **Creator outreach operations**: Use results to support **Figma profile email scraping** campaigns focused on specific creator roles or niches - 📊 **Data analysis & segmentation**: Use the dataset to analyze which keywords/domain combinations produce the most emails for your targeting model *** ### Technical specifications - **Supported Input Formats** - ✅ `keywords` as an array of strings (required) - ✅ `location` as a string (optional) - ✅ `customDomains` as an array of strings (optional) - ✅ `maxEmails` as an integer (optional; range `1` to `10000`) - **Proxy Support** - ✅ Built-in proxy support for reliable scraping (configured internally as part of the actor run) - **Retry Mechanism** - ✅ Includes fallback logic and repeated attempts in case pages return empty/limited results - **Dataset Structure** - ✅ Dataset title: **Figma Emails Dataset** - ✅ Default view: **Scraped Leads** - ✅ Pushed fields (per record): `network`, `keyword`, `title`, `description`, `url`, `email` - **Rate Limits & Performance** - ✅ Uses practical stop conditions (`maxEmails`) and a configurable timeout via **Run Options** - ✅ Designed for incremental saving so long runs don’t lose progress - **Limitations** - ❌ No guarantee that the actor will reach the exact number set in `maxEmails` (it stops when no more suitable results are found) - ❌ Results depend on what’s publicly available for the targeted keywords and domains *** ### FAQ #### Does Figma Email Scraper - Fast, Advanced and Cheapest actually extract emails from Figma? ✅ Yes. The actor extracts email addresses from Figma-related publicly available sources using your provided `keywords` and `customDomains`, then pushes the results into the dataset. #### What input is required to run the actor? ✅ Only `keywords` is required. You can optionally refine results with `location`, filter domains with `customDomains`, and cap results using `maxEmails`. #### Can I limit how many emails I want? ✅ Yes. Use `maxEmails` to set the maximum number of emails to collect. The scraper stops once the limit is reached, and higher limits may take longer. #### Why do I get fewer results than `maxEmails`? ❌ The actor stops when it runs out of suitable results (and it also avoids duplicates). If results are limited, try wider keywords, add similar terms, or include more domains. #### How do I make the leads more targeted? ✅ Use job-title or role-focused `keywords` and set `customDomains` to restrict output to domains that match your outreach intent (for example, `@gmail.com`). #### Can I resume a run if it gets interrupted? ✅ Yes. The actor saves progress (including a cursor and `seen_emails`) so you can continue without starting from scratch. #### What’s the safest way to use these results for outreach? ✅ Always use the data responsibly. Scrape only from publicly accessible sources and ensure your outreach follows applicable privacy rules and platform policies. #### Do you support CSV export or API access? ✅ Dataset export (including JSON/CSV) is available from Apify Console. API-style consumption depends on how you integrate Apify datasets into your pipeline. *** ### Support & feature requests Want to improve **Figma Email Scraper - Fast, Advanced and Cheapest** for your workflow? Tell us what you need next. - 💡 **Feature Requests**: Ideas like CSV export improvements, additional filtering options, or better lead normalization can make your **Figma email scraper tool** experience smoother. - 📧 **Contact**: Reach out at . Your feedback helps shape the roadmap for this **Figma email finder**. *** **Get the most comprehensive, SEO-optimized Figma Email Scraper - Fast, Advanced and Cheapest experience—built for fast lead extraction when you need answers at scale.** ### Disclaimer **This actor accesses publicly accessible sources only.** It does not access private profiles, authenticated data, or password-protected pages. You are responsible for complying with applicable laws and platform terms (including GDPR, CCPA, spam regulations, and any relevant website policies). If you need data removal, contact . Please use this tool responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `keywords` (type: `array`): A list of keywords or queries to search for. ## `location` (type: `string`): Location to filter search results. ## `customDomains` (type: `array`): List of custom email domains ## `maxEmails` (type: `integer`): Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time. ## Actor input object example ```json { "keywords": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "maxEmails": 20 } ``` # 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": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/figma-email-scraper-fast-advanced-and-cheapest").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": [ "manager", "founder", ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com", ], } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/figma-email-scraper-fast-advanced-and-cheapest").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": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }' | apify call solid-scraper/figma-email-scraper-fast-advanced-and-cheapest --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/figma-email-scraper-fast-advanced-and-cheapest", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Figma Email Scraper Fast Advanced And Cheapest", "description": "🚀 Figma Email Scraper Fast Advanced & Cheapest extracts verified emails from design communities—quickly and accurately. Perfect for agencies, B2B sales, and marketers to build targeted lists fast. ⚡🔎 Affordable.", "version": "1.0", "x-build-id": "CKZeh3IhYAvngDRFF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~figma-email-scraper-fast-advanced-and-cheapest/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-figma-email-scraper-fast-advanced-and-cheapest", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~figma-email-scraper-fast-advanced-and-cheapest/runs": { "post": { "operationId": "runs-sync-solid-scraper-figma-email-scraper-fast-advanced-and-cheapest", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~figma-email-scraper-fast-advanced-and-cheapest/run-sync": { "post": { "operationId": "run-sync-solid-scraper-figma-email-scraper-fast-advanced-and-cheapest", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 or Queries", "type": "array", "description": "A list of keywords or queries to search for.", "default": [ "manager", "founder" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "customDomains": { "title": "Enter Custom Email Domains (e.g. @gmail.com, @yahoo.com)", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com", "@yahoo.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "Enter Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.", "default": 20 } } }, "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 } } } } } } } } } } ```