# Youtube Email Scraper (`solid-scraper/youtube-email-scraper`) Actor 📧 Unlock targeted leads with YouTube Email Scraper! Extract emails from creator channels using keywords, niches & locations—fast, accurate, and built for sales, agencies & outreach teams. 🚀 Generate prospect lists instantly and scale smarter. - **URL**: https://apify.com/solid-scraper/youtube-email-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 6 total users, 0 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.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 ### Youtube Email Scraper 📬 **Youtube Email Scraper** is an Apify actor that helps you find and collect contact emails associated with YouTube bios and posts that relate to your chosen keywords. If you’re searching for a **YouTube email scraper**, **scrape YouTube emails**, or an **email harvesting from YouTube channels** tool, this is built for exactly that—whether you’re a marketer, researcher, or data enthusiast. It uses your keywords and email-domain filters to surface relevant leads faster, saving you hours of manual work at scale. --- ### Why choose Youtube Email Scraper? | Feature | Benefit | |---|---| | ✅ **Keyword-driven email discovery** | Find emails tied to YouTube bios and posts related to your keywords in one workflow | | ✅ **Email-domain targeting with customDomains** | Focus results on the domains you care about (for example `@gmail.com`) | | ✅ **Structured, dataset-ready results** | Output consistent fields (`network`, `keyword`, `email`, `url`, etc.) for easy export and analysis | | ✅ **Proxy configuration support** | Run reliably with `proxyConfiguration` and choose the scraping `engine` that fits your needs | | ✅ **Engine choice (cost-effective vs legacy)** | Use `cost-effective` for faster, cheaper scraping or `legacy` for a more traditional approach | | ✅ **Max-results control** | Stop automatically when `maxEmails` is reached to manage time and cost | --- ### Key features - 🔍 **Accurate YouTube email extraction**: Extracts email addresses from publicly available text content associated with YouTube results - 🧠 **Keyword + domain filtering**: Uses your `keywords` plus `customDomains` (email-domain pattern) to narrow down relevant contacts - ⚙️ **Engine selection for different tradeoffs**: Choose between `cost-effective` (residential proxies with async requests) and `legacy` - 🛡️ **Resilience-focused scraping behavior**: Includes retries and fallbacks for blocked or empty-result scenarios to improve run success - 💾 **Real-time dataset saving**: Each found email row is pushed immediately, so progress isn’t lost mid-run - 🌐 **Structured output for downstream use**: Designed for marketers and analysts who want clean fields ready for CRM/import - 🔁 **Progress persistence**: Saves internal progress so long runs can be resumed more safely --- ### Input Provide input via an `input.json` file. Example structure: ```json { "keywords": ["founder", "marketing"], "location": "", "platform": "Youtube", "customDomains": ["@gmail.com"], "maxEmails": 20, "engine": "legacy", "proxyConfiguration": {} } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `keywords` | ✅ Yes | A list of keywords to search for. The scraper uses these keywords to locate relevant YouTube bios and posts. | | `location` | ❌ No | Location to filter search results. Leave empty to not apply a location filter. | | `platform` | ❌ No | Select platform. The only supported enum value is `Youtube` (default: `Youtube`). | | `customDomains` | ❌ No | List of custom email domains to target (example format includes `@gmail.com`). The scraper filters emails by these domains. | | `maxEmails` | ❌ No | Maximum number of emails to collect. The scraper stops once the limit is reached (helps control runtime/cost). Default is `20`. | | `engine` | ❌ No | Choose scraping engine: `cost-effective` (Cost Effective (New)) or `legacy` (Legacy). Default is `legacy`. | | `proxyConfiguration` | ❌ No | Configure proxies for this Actor using Apify proxy settings. | *** ### Output The actor saves each found contact in JSON format by pushing rows to the dataset as results are discovered. Sample output row: ```json [ { "network": "Youtube.com", "keyword": "founder", "title": "Example result title", "description": "Example snippet text where an email was found", "url": "https://example.com", "email": "creator@example.com", "proxyGroups": ["example-proxy-group-or-config"] } ] ``` #### Output Fields | Field | Type | Description | |---|---|---| | `network` | string | The source network label used in output (`Youtube.com`). | | `keyword` | string | The keyword that produced the result. | | `title` | string | Title of the found result item. | | `description` | string | Text snippet/description associated with the result where the email was extracted from. | | `url` | string | URL of the result where the email was found. | | `email` | string | The extracted email address. | | `proxyGroups` | array | Proxy configuration/groups associated with the run (as provided in the input engine/proxy configuration context). | > Note: The actor outputs rows as it discovers emails using `Actor.push_data(row)`; there’s no single “batch summary object” shown in the output schema because each row is pushed independently. *** ### How to use Youtube Email Scraper (via Apify Console) 1. **Open Apify Console**: Log in at https://console.apify.com and open the **Actors** tab. 2. **Find the actor**: Search for **Youtube Email Scraper** and open its details page. 3. **Add your INPUT**: In the INPUT section, paste your `input.json` or use the form fields.\ Set at minimum: `keywords` (required). 4. **Tune targeting**: Add the email domains you want via `customDomains` (for example `@gmail.com`) and optionally set `location`. 5. **Choose an engine**: - `engine: "legacy"` for the legacy approach - `engine: "cost-effective"` for the cost-effective approach 6. **Set output limits**: Adjust `maxEmails` to control how many emails the run collects before stopping. 7. **Configure proxy (optional)**: If you need proxy control, set `proxyConfiguration` in the input. 8. **Run & monitor logs**: Start the run and watch progress in the logs for found emails and retries. 9. **Open the dataset output**: After completion, go to the **OUTPUT** tab, export the dataset from JSON/CSV as needed. No coding required — get accurate results in minutes with **Youtube Email Scraper**. *** ### Advanced features & SEO optimization - 🧩 **Engine-tuned scraping**: **Youtube Email Scraper** supports both `cost-effective` and `legacy` engines so you can balance speed vs reliability depending on your workload. - 🔎 **Email-domain precision for lead generation**: Use `customDomains` (like `@gmail.com`) to improve relevance when you’re building a **YouTube outreach email list**. - 🔄 **Retry and fallback behavior**: Includes retries and handling for blocked or empty-result scenarios to keep long searches running. - 💾 **Progress persistence for larger runs**: Saves progress as it pushes each result, which helps for time-intensive collection sessions. *** ### Best use cases - 📈 **Lead generation for YouTube brands**: Quickly assemble a **YouTube influencer email finder** list filtered by your preferred email domains. - 🎓 **Marketing research & mapping creator networks**: Build a dataset of creator contact emails tied to niche keywords (great for competitor mapping). - 🧠 **Recruiting & partnerships sourcing**: Find outreach-ready contacts for collaborations, guest posts, or partnerships in a specific YouTube ecosystem. - ✉️ **Email marketing list building**: Create a targeted **scrape YouTube emails** dataset to fuel campaigns and enrichment workflows. - 📊 **Data analysis & reporting**: Analyze email distribution by keyword (and your `customDomains`) using structured output fields. - 🛠️ **CRM and automation pipelines**: Feed a consistent JSON structure into downstream systems without manual copy-paste. - 🔍 **YouTube channel email extractor research**: Identify public contact emails associated with YouTube bios and keyword-relevant posts. *** ### 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) - ✅ `engine` as one of: `cost-effective`, `legacy` (optional) - ✅ `proxyConfiguration` as an object (optional) - **Proxy Support** - ✅ Yes, via `proxyConfiguration` - ✅ Engine-specific proxy behavior exists, depending on whether you select `cost-effective` or `legacy` - **Retry Mechanism** - ✅ Includes retries and fallbacks to reduce disruptions from blocked or empty results - **Dataset Structure** - ✅ JSON rows pushed per discovered email with fields: `network`, `keyword`, `title`, `description`, `url`, `email`, `proxyGroups` - **Rate Limits & Performance** - ✅ `maxEmails` helps control runtime by stopping once the limit is reached - ✅ Large searches may take longer (you can increase Run Options timeout in Apify for bigger tasks) - **Limitations** - ❌ Emails are collected only when they appear in publicly available content associated with the discovered results - ❌ Higher email limits don’t guarantee reaching the exact `maxEmails` count *** ### FAQ #### Can the Youtube Email Scraper extract emails from private or logged-in pages? ❌ No. **Youtube Email Scraper** is designed to work with **publicly available sources**. It does not access private profiles or password-protected data. #### What email addresses will I get—any emails or only specific domains? It extracts emails and filters them by the domains you provide in `customDomains`. This is how you implement domain-level targeting for more relevant outreach, such as building a **YouTube contact info scraper** dataset for your preferred email providers. #### What input fields are required? ✅ Only `keywords` is required. Everything else (`location`, `platform`, `customDomains`, `maxEmails`, `engine`, and `proxyConfiguration`) is optional. #### Which engine should I choose: cost-effective or legacy? If you want faster and more cost-efficient runs, choose `engine: "cost-effective"`. If you prefer the legacy approach, use `engine: "legacy"`. You can also switch engines if you notice results are unexpectedly low. #### How many emails will the actor collect? The actor will stop when it reaches `maxEmails`. However, it doesn’t guarantee it will always reach that number—if fewer matching emails are found, the run may end earlier. #### Is there structured output I can import into other tools? ✅ Yes. Each dataset row contains consistent JSON fields: `network`, `keyword`, `title`, `description`, `url`, `email`, and `proxyGroups`, which makes it easy to export to JSON/CSV and integrate into workflows. #### Do I need to configure proxies? Not necessarily. You can run without custom proxy configuration, or you can provide `proxyConfiguration` and choose the `engine` value that best fits your use case. #### Is this good for YouTube lead generation tool workflows? ✅ Yes. This **YouTube email search tool** is commonly used to compile a **YouTube outreach email list** filtered by keywords and `customDomains`, which is ideal for lead generation and enrichment pipelines. *** ### Support & feature requests If you have questions about the **Youtube Email Scraper**, or ideas to improve the YouTube email scraper experience, share your feedback. - 💡 **Feature Requests**: Want enhancements like additional export formats, more filtering options, or improved result fields? Tell us what would matter most for your **YouTube channel email extractor** workflow. - 📧 **Contact**: Reach out at . Your feedback helps shape the roadmap for improving **Youtube Email Scraper**. *** ### Disclaimer **This tool accesses only publicly accessible sources.** It does not access private profiles, authenticated data, or password-protected pages. It’s your responsibility to comply with applicable laws (including GDPR/CCPA where relevant), spam regulations, and each platform’s terms of service. For data removal requests, contact . Please use **Youtube Email Scraper** responsibly, ethically, and for legitimate purposes only. *** *If you’re building a scalable **Youtube Email Scraper** workflow, this is one of the most comprehensive and SEO-optimized ways to extract publicly available YouTube-related contact emails using keywords and domain targeting.* # 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 ## `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. ## `engine` (type: `string`): Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `proxyConfiguration` (type: `object`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "founder", "marketing" ], "location": "", "platform": "Youtube", "customDomains": [ "@gmail.com" ], "maxEmails": 20, "engine": "legacy" } ``` # 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": [ "founder", "marketing" ], "location": "", "customDomains": [ "@gmail.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/youtube-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": [ "founder", "marketing", ], "location": "", "customDomains": ["@gmail.com"], } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/youtube-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": [ "founder", "marketing" ], "location": "", "customDomains": [ "@gmail.com" ] }' | apify call solid-scraper/youtube-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/youtube-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Email Scraper", "description": "📧 Unlock targeted leads with YouTube Email Scraper! Extract emails from creator channels using keywords, niches & locations—fast, accurate, and built for sales, agencies & outreach teams. 🚀 Generate prospect lists instantly and scale smarter.", "version": "0.0", "x-build-id": "tBz2kdrQUoOQ03e5W" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~youtube-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-youtube-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~youtube-email-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-youtube-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~youtube-email-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-youtube-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "founder", "marketing" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "platform": { "title": "Platform", "enum": [ "Youtube" ], "type": "string", "description": "Select platform.", "default": "Youtube" }, "customDomains": { "title": "Custom Email Domains", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "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 }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "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 } } } } } } } } } } ```