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YouTube comment grabber
AI-powered public opinion data mining assistant

Eliminate the need for complex Python scripts, effortlessly penetrating the data fog. Combined with DICloak's professional fingerprint anti-association technology, you can safely and efficiently capture comments under specific YouTube videos using only natural language commands. Transform user feedback into structured data in an instant, aiding in in-depth market research and sentiment analysis.

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Crawl Youtube video comments

How to Use YouTube Comment Scraper (MCP RPA): From Conversation to Insight

Simplify tedious data scraping into a simple conversational interaction. Connect your AI editor (e.g., Cursor/Claude) with the DICloak fingerprint browser via the MCP protocol. AI understands your collection needs (such as quantity, sorting method) and automatically commands the browser to simulate human scrolling and extraction, obtaining real user voices without configuring APIs.

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Step 1: Connect and configure

Make AI connections Configure DICloak MCP Server with one click in Claude Desktop or Cursor. Make sure that the DICloak client is up and ready for the fingerprint environment to access YouTube.

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Step 2: Prompt

Natural language control Describe your acquisition goals directly. For example: "Please call the 'US_Analyst_02' environment to access the YouTube video [insert URL]. Help me sort the comment section by 'latest' and collect the top 50 comments. Please focus on extracting the commenter's username, comment content and number of likes, and filter out emoji-only comments containing emojis, and finally organize them into a table for me. "

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Step 3: Execute and deliver intelligently

Automated collection and cleaning AI Agent will take over the browser, simulate human reading and scrolling behavior, and scrape comment data. After the collection is completed, AI can clean, classify, or generate sentiment analysis reports directly in the dialogue window, realizing "collection-analysis" in one step.

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Who Should Use YouTube Comment Scraper (MCP RPA)?

1. Brand and market researcher

Solve the pain point: public opinion monitoring. Quickly collect user reviews under competing videos, analyze consumers' real attitudes towards specific features or products, and discover potential market opportunities or pain points.

2. Content Creators (YouTubers)

Solve pain points: fan interaction management. Batch export comments on your popular videos, using AI to quickly filter out high-quality viewer questions or suggestions as a source of material for your next Q&A video.

3. Sentiment Analysis Specialist (NLP)

Solve pain points: difficulty in obtaining corpus. Get a real, living corpus of social media. Collect large amounts of comment data and train or fine-tune sentiment analysis models to gain insights into public sentiment trends.

4. Cross-border e-commerce product selector

Solve pain points: requirements validation. Collect user discussions under relevant product review videos to understand the target audience's specific slots (e.g., "battery non-durable") and expectations for the product, and assist in product improvement and selection.

Why is YouTube Comment Scraper (MCP RPA) the best choice for your needs?

"Talking to people" is code

Traditional crawlers need to deal with complex AJAX loading and backcrawling strategies. MCP RPA lets you just give commands as if you were talking to an assistant, and the AI automatically handles page scrolling (infinite scrolling) and DOM element positioning.

The ultimate in anthropomorphic security

Crawling reviews at scale can easily trigger Google's CAPTCHA. The tool runs in the DICloak fingerprint environment, with anthropomorphic scroll speed and mouse tracks, which greatly reduces the risk of being identified as a robot and ensures business continuity.

Data privacy guarantees

All collection processes run locally on your device, and raw data goes directly into the context of your AI editor without going through any third-party cloud storage, keeping your research data and trade secrets safe.

Seamless AI ecosystem integration

Perfect for Claude Desktop and Cursor. You no longer need the tedious process of "Collect Data -> Export Excel -> Import AI". The collected comments are immediately "read" by AI and summarized and analyzed.

Frequently asked questions about YouTube Comment Scraper (MCP RPA).

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How fast is the collection? How many strips can be collected?

The speed depends on your web and browser's rendering speed. Theoretically, the number of collections can be controlled by Prompt (e.g., 100, 500). The AI automates the rolling load operation until the quantity requirements are met.

Will my Youtube account be banned?

Extremely secure. Because we use DICloak's isolated fingerprint environment and simulate front-end browsing behavior (non-back-end API brute force), it is very account-friendly. It is recommended to maintain a reasonable frequency when collecting.

Can I collect replies?

Yes. You can explicitly request in your prompt "Please expand the responses under each comment and capture them together". The AI will try to click the "View replies" button for deeper interactive content.

What AI clients are supported?

Currently, Claude Desktop and Cursor, which integrate the MCP protocol, are mainly supported. This allows data acquisition and data analysis to be done seamlessly within the same window.

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