Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Fetch a real product's current price, stock, rating, or images from retailer pages over the Apify MCP server, and return them as typed fields rather than prose. Use when someone asks what a product costs right now, whether it is in stock, how it is rated, to compare a product across retailers, or to check a product URL they pasted. Also use when an agent would otherwise answer a product question from training data. Not for managing your own store's catalog, not for payments, and not for questions answerable without live retailer data.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
A model answers product questions from training data that was fixed months ago, or by reading a page as prose with no product fields. This skill routes the question to a hosted Actor that reads retailer pages on request and returns structured records: price, currency, stock, rating, image URLs, and a link.
Written by a product marketing manager at Apify. It calls E-commerce Scraping Tool, a paid first-party Apify Actor, so weigh the framing accordingly. Everything below is what testing against the live Actor returned, including where it does not work.
The MCP endpoint is https://mcp.apify.com. Appending
?tools=apify/e-commerce-scraping-tool narrows the server to this one Actor, which makes
tool selection more reliable when product data is the only job. Authentication is OAuth on
first use for interactive clients, or a bearer token for unattended ones. An Apify account
is required and the Actor is paid, billed per run started plus per product returned.
| The question | Input to send |
|---|---|
| About a specific page the user gave you | detailsUrls: [{"url": "..."}] |
| "Find me an X under $Y" with no URL | keyword plus marketplaces |
| "Compare X across stores" | keyword plus several marketplaces |
Always send maxProductResults and additionalProperties: true. Without the second,
stock, rating, list price and identifiers are all missing, because they are nested there
rather than at the top level.
apify--e-commerce-scraping-tool (two hyphens, not a slash). It returns run
metadata and a datasetId. It does not return products.status. If it is not SUCCEEDED, call get-actor-run with the runId and
a waitSecs until it is. The Actor tool returns when its own wait window elapses, not
when the run finishes, so RUNNING is a normal answer and the dataset holds nothing at
that moment.get-dataset-items with the datasetId, a limit, and fields.Two failures live here. Stopping after step 1 returns a result that reads like success and holds no product data. Skipping step 2 fetches an empty dataset and reports the product as not found, intermittently, depending only on how fast the retailer answered.
The full record is large: one Amazon product measured about 88 KB across 142 fields, most
of it marketing content and review text. Pass fields in dot notation, naming only what
the question needs.
Projected output comes back flat. The dots stay in the key names, so it is
item["offers.price"], not item["offers"]["price"]. Walking the nested path against a
projected response finds nothing, which is indistinguishable from the retailer not
reporting the field.
The four differences that bite hardest:
offers.price is a number on some retailers and a string on others.offers.priceCurrency on some and offers.currency on others, and the value
may be a symbol or an ISO code.additionalProperties, as inStock and stars, not at the
top level. Top-level rating was null on a product whose stars was 4.2.brand frequently carries marketing text such as Visit the Sony Store rather than a
brand name.marketplaces enum arrives truncated over MCP, because the server caps how many
characters of a long enum it forwards. Measured on 2026-08-27: of 249 values, 122 fit and
127 were dropped. A validation error naming marketplaces means the retailer cannot be
named in a keyword search on this connection, not that it is unsupported. Use
detailsUrls, which takes arbitrary URLs and is unaffected.additionalProperties and two other retailers returned 4,
with stock and rating absent on every record from one of them. There is no unified schema
to rely on.maxProductResults. Prefer one call with several URLs or marketplaces
over several calls, and never re-run to check a result you already have.additionalProperties can reach roughly 100 KB for one product. Never paste it into
a reply.rating or stars of 0 means absent, not a zero-star product.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
日本語の概要は準備中です。原文の説明を表示しています。
Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
日本語の概要は準備中です。原文の説明を表示しています。
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
日本語の概要は準備中です。原文の説明を表示しています。
Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。