amzscout-skill-mcp
AMZScout Skill + MCP AI-powered Amazon product research and market analysis, right from your MCP client.
Что умеет
- Amzscout Analyze Product: Full raw data for a single Amazon product by ASIN — price, estimated sales/revenue, reviews, rating, listing quality, sellers, plus sales/price/revenue history when available
- Amzscout Analyze Niche: Market snapshot for an Amazon niche/keyword — top products by revenue plus computed aggregates (price/sales/revenue/review distributions, revenue concentration, brand spread).
- Amzscout Compare Products: Side-by-side raw data for 2–5 Amazon products by ASIN — price, sales/revenue estimates, reviews, listing quality, plus history when available. Pure data fetch (no AI analysi
Какие данные видит
Нужен ли аккаунт
Нужен API-ключ из настроек сервиса
AMZScout Skill + MCP
AI-powered Amazon product research and market analysis, right from your MCP client.
What you can do
- Product research - analyze any Amazon product by ASIN: price, estimated sales, revenue, and reviews
- Niche analysis - evaluate a market or keyword niche, including competition and demand
- Product comparison - compare 2–5 products or niches side-by-side
- Keyword & SEO data - pull keyword and PPC insights for a product or niche
- Brand lookup - find all products listed under a specific Amazon brand
Requirements
You'll need an AMZScout API key. [Get one here] (https://learn.amzscout.net/amazon-product-api-for-ai-agents).
Как подключить
Как подключить amzscout-skill-mcp к Claude
Адрес сервера, который нужно вставить в настройках Claude:
https://amzscout-skill-mcp.run.tools
- Откройте Claude (сайт claude.ai или приложение для компьютера).
- Перейдите в Настройки → Коннекторы (в английском интерфейсе: Settings → Connectors).
- Нажмите Добавить пользовательский коннектор (Add custom connector).
- Вставьте адрес сервера, скопированный ниже, в поле URL удалённого MCP-сервера и нажмите Добавить.
- В чате нажмите + → Коннекторы и включите новый коннектор.
Пользовательские коннекторы доступны на тарифах Free, Pro, Max, Team и Enterprise. На Free можно добавить только один. В Team и Enterprise коннектор сначала добавляет владелец организации в Настройки организации → Коннекторы.
Авторизация
После нажатия Добавить откроется окно входа в сервис. Войдите под своим аккаунтом и подтвердите доступ. Пароль Claude не видит.
Как подключить amzscout-skill-mcp к ChatGPT
Адрес сервера, который нужно вставить в настройках ChatGPT:
https://amzscout-skill-mcp.run.tools
- Откройте ChatGPT в браузере (chatgpt.com). Нужен тариф Plus, Pro, Business, Enterprise или Edu.
- Один раз включите режим разработчика: Настройки → Приложения → Дополнительные настройки → Режим разработчика (Settings → Apps → Advanced settings → Developer mode).
- Откройте Настройки → Коннекторы и нажмите Создать (Create).
- Заполните форму: Название (любое), Описание (одна фраза, что делает сервис), URL MCP-сервера (скопируйте ниже).
- В поле Аутентификация выберите OAuth, если сервис требует вход, иначе Нет. Нажмите Создать.
- В новом чате откройте + → Приложения/Коннекторы и включите коннектор.
Название раздела у OpenAI менялось (Connectors → Apps/Plugins). Если пункт называется иначе, ищите «режим разработчика» в настройках. В рабочих пространствах Business/Enterprise администратор должен разрешить пользовательские коннекторы.
Авторизация
При первом использовании ChatGPT откроет окно входа в сервис. Войдите и подтвердите доступ.
Как подключить amzscout-skill-mcp к Cursor
Адрес сервера, который нужно вставить в настройках Cursor:
https://amzscout-skill-mcp.run.tools
Быстрый способ: нажмите кнопку Открыть в Cursor ниже, Cursor сам предложит добавить сервер.
Вручную:
- В Cursor откройте Settings → Cursor Settings → MCP и нажмите Add new global MCP server.
- Вставьте JSON, скопированный ниже, в открывшийся файл
~/.cursor/mcp.json(для одного проекта:.cursor/mcp.jsonв корне проекта). - Сохраните файл. Сервер появится в списке MCP; при необходимости пройдите авторизацию по кнопке рядом с ним.
Авторизация
Если сервис требует вход, рядом с сервером в списке MCP появится кнопка авторизации.
Список инструментов сервера (12)
Технические названия из tools/list. Нужны только разработчикам.
| amzscout_analyze_product | Full raw data for a single Amazon product by ASIN — price, estimated sales/revenue, reviews, rating, listing quality, sellers, plus sales/price/revenue history when available. Pure data fetch (no AI analysis) — reason over the returned data yourself. How to use: audit the product like a sourcing analyst — demand trend & seasonality from sales history, pricing direction & margin risk from price history and FBA fees, competition from sellers/reviews, listing quality from LQS, then conclude whether a new seller should enter (GO / NO-GO and what it would take). |
| amzscout_analyze_niche | Market snapshot for an Amazon niche/keyword — top products by revenue plus computed aggregates (price/sales/revenue/review distributions, revenue concentration, brand spread). Pure data fetch (no AI analysis) — reason over the returned data yourself. How to use: judge niche attractiveness — demand concentration (revenueTop5SharePercent: high = winner-takes-all, low = fragmented/open), price bands and where the money sits, review counts as entry moats, brand dominance vs no-name spread, and standout products (high sales + weak rating/reviews = displacement opportunity). |
| amzscout_compare_products | Side-by-side raw data for 2–5 Amazon products by ASIN — price, sales/revenue estimates, reviews, listing quality, plus history when available. Pure data fetch (no AI analysis) — do the comparison yourself. For a single ASIN, analyzeProduct is the equivalent. How to use: compare demand (est. sales), revenue, review moat and rating, price positioning, listing quality, and history trends (growing vs declining), then give a verdict on which product is the stronger opportunity and why. |
| amzscout_compare_niches | Raw head-to-head data for 2–5 Amazon niches / category keywords — per-niche product sets plus computed aggregates (price/sales/revenue distributions, revenue concentration, brand spread). Pure data fetch (no AI analysis) — do the comparison yourself. For ASINs, compareProducts is the equivalent. How to use: weigh demand (total est. revenue/sales) against competition (review levels, brand concentration) and price levels per niche, then give a verdict on which niche is the better opportunity for a new seller and under what conditions. |
| amzscout_analyze_product_set | Raw data across an explicit set of 2–100 ASINs — product rows plus computed aggregates (price/sales/revenue/review distributions, revenue concentration, brand spread). Pure data fetch (no AI analysis) — reason over the returned data yourself. To discover products from a keyword instead, analyzeNiche is the equivalent. How to use: treat the set as a mini-market — segment products into groups, spot where demand concentrates, flag outliers (price, sales, review anomalies), and summarize group-level signals. |
| amzscout_search_products | Keyword search against Amazon — returns the top N products with price, sales, revenue, reviews, rating. Pure data fetch (no AI analysis). Best when you need raw product rows (specific sort order or filters); analyzeNiche additionally returns computed market aggregates on top of the rows. How to use: scan the rows for demand leaders, price clusters, and low-review listings that still sell — those are the entry-opportunity signals. |
| amzscout_find_by_brand | List products under a specific Amazon brand. Pre-validates the brand name via cached AI check, then filters keyword-search results to rows whose `brand` field actually matches. On no-match, returns the brands that did appear in the keyword pool so callers can suggest alternatives. How to use: assess the brand's Amazon footprint — lineup breadth, price range, which products carry the revenue, and how strong its review moat is. |
| amzscout_get_keywords | Amazon keyword / SEO / PPC data for either a single product (ASIN-scope — terms the product ranks for) or a niche/category (keyword-scope — search data around the term). Returns keyword rows with search volume, CPC, and competition where available. Pure data fetch (no AI analysis). How to use: pick high-volume / low-competition terms for SEO and PPC targeting, use CPC as ad-cost pressure, sum search volumes to gauge niche demand, and for ASIN-scope check organic vs sponsored ranks to spot listing-optimization gaps. |
| amzscout_search_knowledge | TF-IDF search across the AMZScout knowledge base (Amazon-seller tutorials, brand reference, glossary). Returns the top-K relevant chunks with title, source URL and text. Use this to ground answers in factual material. |
| amzscout_recommend_tool | Given a user use-case, returns the AMZScout tools & Sellerhook services catalog (with tracking links) so you can recommend the right AMZScout product/feature. Use for "which AMZScout tool should I use for X" questions. |
| amzscout_usage | The caller's AMZScout AI-agents token balance — remaining, used, and limit. Free — no tokens are charged for this call. How to use: answer "how many tokens do I have left", "what's my usage / balance / limit", or when a call fails on quota. Report the remaining figure first. |
| amzscout-agent | AMZScout all-in-one Amazon research assistant. Ask anything in natural language ("Is B07GQF9D1Z worth selling?", "Analyze the yoga mat niche", "Find products for brand Anker") and it returns a finished analysis — it pulls live Amazon data and runs the right analyses internally, so no sub-tool selection is needed. Best for a hands-off answer; the granular amzscout_* tools are the alternative when step-by-step orchestration is preferred. Returns a complete, user-ready report. |