# Amazon Agent Crawl MCP Canonical page: https://www.kuudo.com/docs/amazon-agent-crawl/ Amazon Agent Crawl MCP lets connected agents search Amazon, open product detail pages, extract listing facts, and compare products from current page data. ## What Agent Crawl Does **Agent Crawl** is a crawling and extraction stack aimed at **real websites**, not static copy-paste. You can run it from a **command line**, **Docker**, or wire it up as an **MCP server** so an AI assistant can call it like any other tool. Under the hood it builds on **crawl4ai**-style browser crawling: it can load pages the way a user’s browser would, respect sensible rate limits, optionally use stealth-friendly settings for difficult sites, and save **RAG-ready** text (markdown, cleaned HTML, chunks) for search and Q&A pipelines. In practice it helps you: - **Crawl** a single page or many linked pages with strategies (breadth-first, depth-first, scored links, adaptive “stop when you know enough” runs). - **Shape output** with topics, search-style filters, chunk sizes, and optional deep-crawl limits so results fit retrieval or summarization. - **Extract structure** where templates exist, so a page becomes **fields** (titles, prices, specs) instead of one big blob of HTML. Packaged flows, including **Amazon** product and search helpers, sit on top of that core: same engine, opinionated defaults for a specific class of pages. ## Why Agents Use It Models are strong at language and reasoning but **weak guarantees** on facts about the live web: training data goes stale, URLs change, and “what I remember about this product” is not the same as “what Amazon shows today.” Agent Crawl gives an agent **repeatable tools** that fetch and normalize **current** pages. That reduces invention on prices, availability, and specs, and turns “describe this URL” into a **grounded** step the user can audit. For agents specifically, the value is: - **Grounding**: answers tied to a fetch the user or tool chain can trace back to a real page. - **Structure**: listings become comparable records, such as search rows or product fields, instead of prose-only summaries. - **Composable workflows**: search, then open several PDPs, then summarize. The same pattern works for docs sites, support portals, or internal wikis when you use the general crawl tools; Amazon is one high-leverage example. The sections below are written for **you in chat**: concrete prompts and outcomes. The assistant is the one invoking Agent Crawl on your behalf when those tools are connected. ## How to Ask You’re in a **normal chat** with an assistant that can use **Amazon lookup tools** on your behalf (for example in Claude, ChatGPT, or another app that supports the same kind of connector). You describe what you want; you do **not** need to know how the tools work under the hood. **What helps every time** - Paste the **full product link** from your browser when you mean one exact listing (the address bar URL from Amazon). - Say **how many** items matter to you (“top three results”, “first dozen hits”). - Say what you care about: **price only**, **full specs**, **reviews**, **questions & answers**, **images**, and so on. Amazon’s pages are built for shoppers, not for robots. Sometimes a field is missing or a page is partly blocked; if that happens, ask again with a narrower question or a different link. **Continuing in the same chat** - You can say **“same link, but now include reviews”** or **“here’s a second URL — compare the two”** without managing anything technical yourself. - If the answer felt thin, say **“open the full listing details”** or **“only the spec table”** so the assistant knows to go deeper on the next pass. --- ## Product Page Prompts Use this when you have a **single** Amazon product URL and want facts from that listing pulled into the conversation. ### Example: “Should I buy this for my desk?” **You might write** > I’m looking at this standing desk converter. Here’s the link: [paste URL]. Pull the title, current price, whether it says in stock, the bullet features, and the weight capacity or size from the details. Summarize in three pros and two cons for someone who works 8 hours a day. **What you should get** - A short summary grounded in that page: price, availability-style wording, key bullets, dimensions or weight limits if the listing shows them, and a balanced opinion framed from those facts. ### Example: “Will this fit in my bag?” **You might write** > [paste URL] - This is a portable monitor. I need the **package dimensions** and **item weight** from the product details, and whether the stand folds flat. Tell me if it’s realistic for a 15" laptop backpack. **What you should get** - Numbers or clear “not listed on the page” answers, plus a plain-English take on carryability. ### Example: “What are people complaining about?” **You might write** > Same link as before. **Include customer reviews** — up to about 20. Group themes: shipping, quality, setup difficulty, anything recurring. Don’t quote long rants; paraphrase. **What you should get** - Themes from recent reviews, not a dump of every star rating. ### Example: “Does anyone answer ‘X’ in the Q&A?” **You might write** > [paste URL] - Turn on **Q&A** if you can. I need to know whether this router works with my ISP’s modem-only setup. Quote or paraphrase only relevant Q&A. **What you should get** - Answers drawn from the Questions & Answers section when the listing has them. ### Example: “Images for a slide deck” **You might write** > [paste URL] — I need **product image links** (main image and gallery if available), plus the official product name as Amazon shows it. One bullet list, no essay. **What you should get** - A tidy list of titles and image URLs you can reuse (respect copyright and Amazon’s rules for how you publish them). ### Example: “Skip the fluff — title, price, Prime?” **You might write** > [paste URL] — Just **title, price, rating, review count**, and whether it looks Prime-eligible. One short paragraph. **What you should get** - A compact fact card, no long spec tables unless you ask for them. --- ## Amazon Search Prompts Use this when you want a **list of options** from a search, like typing into Amazon’s search box, but explained in chat. ### Example: “Shortlist under a budget” **You might write** > Search Amazon for **wireless earbuds under $50** (use whatever filters the search naturally applies). Give me up to **12** results in a **table**: name, price, star rating, approximate review count, Prime yes/no, and mark which ones say **Sponsored** if that’s visible. **What you should get** - A scannable table or list you can sort mentally by price or rating, with sponsored items called out so you’re not comparing ads to organic results by mistake. ### Example: “What exists in this category?” **You might write** > Search for **mechanical keyboard hot swap 75%**. I’m not loyal to a brand — I want **10** options with **price** and **rating**. Highlight any that look like a strong default pick for a first mechanical keyboard. **What you should get** - A curated-feeling shortlist with enough variety to continue in a follow-up message (“now open the top three and compare switches” — see the next section). ### Example: “Find me a gift pattern” **You might write** > Search Amazon for **gifts for a hobby gardener under $30**. List **8** concrete products (not generic categories) with price and one-line “why it’s a nice gift.” **What you should get** - Concrete product names and prices tied to the search, ready to refine (“remove tools they already own” in a follow-up). ### Example: “Compare delivery promises at a glance” **You might write** > Search **USB-C hub pass-through charging MacBook**. Return **15** results; for each, include **price** and any **delivery** snippet the search card shows. **What you should get** - Enough rows to see which listings emphasize fast shipping vs. lowest price. --- ## Search Then Compare Prompts Use this when you want the assistant to **run a search**, then **open the first few product pages** and pull the richer detail you’d get by clicking each listing (spec tables, long descriptions, sometimes reviews depending on what you asked). ### Example: “Pick the best warranty among the top hits” **You might write** > Search **electric kettle glass no plastic contact water**. Then open the **top 4** product pages. For each kettle, extract **warranty** and **materials / BPA-free** language from the listing. End with a recommendation: best for someone who cares about plastic touching hot water. **What you should get** - Side-by-side facts from full pages, not only the thin search snippet. ### Example: “Noise cancelling — battery life battle” **You might write** > Search **over ear noise cancelling headphones** and open the **top 3** results. From each full product page, pull **battery life** claims and **USB-C vs micro-USB** charging. Table + one winner for long flights. **What you should get** - Comparable numbers or quoted phrases as shown on each PDP, with a clear comparison. ### Example: “Monitor arms — will they hold my display?” **You might write** > Search **monitor arm single 32 inch VESA**. Open **top 5** listings. From each page, get **max weight** and **max screen size** if stated. Flag any mismatch with a 32" 9 lb monitor. **What you should get** - A compatibility-oriented matrix and a short “safe / risky / unknown” readout. ### Example: “Baby gear — narrow after reading details” **You might write** > Search **video baby monitor no WiFi**. Open the **top 3** products. From full pages, list **range**, **battery**, and whether **WiFi is required** or optional. Then tell me which one matches “apartment, two rooms, paranoid about hacking.” **What you should get** - Specs that rarely fit in search cards, plus a reasoned pick aligned to your constraints. ### Example: “Same search, but I only trust deep specs” **You might write** > Search **portable SSD 2TB**. Open **top 4** pages. I care about **read/write speeds** and **IP rating** if any. Build a comparison table; if a field isn’t on the page, say “not stated.” **What you should get** - Honest gaps (“not stated”) instead of guessed numbers. --- ## Limits and Expectations - Listings are fetched as Amazon serves them, often **amazon.com (US)**. Prices, wording, and availability are **what the page showed at lookup time**, not a live cart or checkout. - **Sponsored** products appear in search; ask the assistant to **label** them when you’re comparing. - Heavy automation can hit **captchas or empty sections**; retry later, try another product link, or ask for a smaller slice of the page (e.g. title + price only). Use these tools for **personal research and drafting** (gift lists, spec checks, comparison notes). Respect **Amazon’s terms** and **local rules** for scraping or automated access; don’t use this to hammer the site or replace Amazon’s own apps for purchasing.