Use Cases
01Quick Answer
Use scrape_template (1 credit) to pull reviews from Amazon, YouTube, or Hacker News with no selectors to maintain, reddit_search (5 credits) for Reddit discussions via community archives, analyze_content (3 credits) for sentiment, topics, and entities, and summarize_content (4 credits) for a briefing. About 13 credits per product, cheap enough to run weekly.
02The brief
Customer sentiment is scattered across Amazon listings, Reddit threads, and Hacker News comments. Reading it manually means you notice a quality problem weeks after the reviews turned, and marketplace redesigns break selector-based scrapers constantly.
CrawlForge scrape_template pulls clean data from known sites -- Amazon products, YouTube, Hacker News -- with no selectors to maintain, and reddit_search reads Reddit discussions through community archives, since reddit.com blocks scrapers. analyze_content scores sentiment, topics, and entities, and summarize_content turns the pile into a briefing.
03In code
1// Pull reviews from known sites without writing selectors2const product = await mcp.scrape_template({3 template: "amazon-product",4 url: "https://www.amazon.com/dp/B0EXAMPLE",5});6 7// reddit.com blocks scrapers -- reddit_search reads the community archives8const reddit = await mcp.reddit_search({9 query: "Example Gadget",10 subreddit: "gadgets",11 limit: 10,12});13 14const voices = product.reviews.map(r => r.text).join("\n");15 16// Sentiment, topics, and entities across every review17const analysis = await mcp.analyze_content({18 text: voices,19 options: { includeSentiment: true, extractTopics: true, extractEntities: true },20});21 22// One briefing for the product team23const digest = await mcp.summarize_content({24 text: voices,25 options: { summaryLength: "medium", summaryType: "abstractive" },26});27 28console.log(reddit.count, reddit.results[0]?.num_comments); // discussion volume29console.log(analysis.sentiment, analysis.topics);30console.log(digest.summary);04The pipeline
05Questions
04
Use scrape_template with a built-in template such as amazon-product, and reddit_search for Reddit discussions -- reddit.com blocks direct scraping, so reddit_search reads the community archives instead. CrawlForge maintains the extraction rules, so a marketplace redesign does not quietly break your pipeline the way custom selectors do.
Amazon products, LinkedIn profiles, GitHub repos, YouTube videos, tweets, Reddit threads, the Hacker News front page, Product Hunt launches, Stack Overflow questions, and npm packages. Call scrape_template with template "list" to see the current set. For Reddit, prefer reddit_search -- reddit.com blocks direct scraping, so the reddit-thread template no longer works reliably.
analyze_content returns a sentiment score, detected language, topics, named entities, and readability for the text you pass in. Feed it the combined reviews, then run summarize_content for a short briefing on what changed.
About 13 credits per product per run: 1 for each scrape_template call, 5 for reddit_search, 3 for analyze_content, and 4 for summarize_content. Monitoring 10 products weekly is roughly 560 credits a month.
06Keep exploring
Gather competitor data discreetly using stealth browsing and structured extraction. Watch pricing, messaging, and launches without tripping bot defenses.
Track competitor prices and product availability across hundreds of e-commerce sites. Detect undercutting the day it happens and reprice with confidence.
Start forging
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