# Amazon Search Monitor — New Product Alerts (Vigia) (`om_kh/vigia-amazon-keyword-monitor`) Actor Monitor an Amazon search or category and get only NEW products since last check, with an entrant-velocity spike signal. Catch new competitors entering your niche. Charged only on new products, never per run. Ideal for e-commerce and market-intel agents. - **URL**: https://apify.com/om\_kh/vigia-amazon-keyword-monitor.md - **Developed by:** [omar khandji](https://apify.com/om_kh) (community) - **Categories:** E-commerce, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Amazon Search Monitor — New Product Alerts (Vigia) > Monitor an Amazon search or category and get only NEW products since last check, with an entrant-velocity spike signal. Catch new competitors entering your niche. Charged only on new products, never per run. Ideal for e-commerce and market-intel agents. ### What it does Catch new products entering an Amazon search or category. You get **only what changed since your last check** — never a full re-dump to diff yourself. ### Why Vigia — 5 advantages a raw scraper can't match 1. **Charged only on real change.** You pay for new products since the last check — a run where nothing changed costs **$0**. Raw scrapers bill every run or every row regardless. 2. **Never billed on a failed source.** The source check is charged only when the source actually responded. If it's down, you don't pay for our outage. 3. **Append-only delta + spike signal.** The first monitored run stores a free baseline; later runs deliver only what's new, plus a velocity-spike alert when volume suddenly surges (trend / review-bomb / hiring-surge). 4. **Hard cost cap you control.** Set `maxTotalChargeUsd` and the run can never bill above it — predictable spend, no surprise invoice. 5. **Agent-ready output.** Clean, normalized rows and a `RUN_SUMMARY.json` with ready-to-use signals — chainable from any MCP / A2A agent in one step. ### Example input ```json { "searchUrls": [ "https://www.amazon.com/s?k=standing+desk" ], "monitorEnabled": true, "maxTotalChargeUsd": 1.0 } ```` Set `monitorEnabled: true` so the first run stores a free baseline and later runs return only new results. Pin a `monitorId` to keep separate targets from sharing state. ### Output Each row is a normalized change record: `record_id`, `query_id`, `title`, `url`, `author`, `published_at`, `score`, `text`. A `RUN_SUMMARY.json` accompanies every run with the aggregated signal (counts, velocity spikes, trend). ### How you're charged - **Product alert** — billed once per new product since the last check. - **Source check** ($0.12) — billed once per monitored target, **only when the source responded**. A failed source is free. - **A no-change run costs $0.** Vigia never scrapes the source itself; it chains a licensed scraper, caps every call, and passes you only the delta. *** *Part of the Vigia monitoring suite — change-only billing, outage-safe, agent-ready.* # Actor input Schema ## `searchUrls` (type: `array`): Amazon search or category URLs to monitor for new products. ## `currentItems` (type: `array`): Skip the chained fetch and pass records directly (no upstream call, no fetch fee). ## `maxTotalChargeUsd` (type: `number`): Hard maximum amount that this run may charge. ## `sources` (type: `array`): Declare every upstream source before this run. Each item needs name, authorization, and estimated\_cost\_usd. ## `monitorEnabled` (type: `boolean`): The first monitored run stores a free baseline. Later runs deliver and charge only new results. ## `monitorId` (type: `string`): Pins the persistent baseline to a name of your choice, so separate targets never share state. Leave empty to derive it automatically. ## Actor input object example ```json { "searchUrls": [ "https://www.amazon.com/s?k=standing+desk" ], "currentItems": [], "maxTotalChargeUsd": 1, "sources": [ { "name": "Chained upstream actor", "authorization": "public_structured_data", "estimated_cost_usd": 0 } ], "monitorEnabled": false, "monitorId": "" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchUrls": [ "https://www.amazon.com/s?k=standing+desk" ] }; // Run the Actor and wait for it to finish const run = await client.actor("om_kh/vigia-amazon-keyword-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchUrls": ["https://www.amazon.com/s?k=standing+desk"] } # Run the Actor and wait for it to finish run = client.actor("om_kh/vigia-amazon-keyword-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchUrls": [ "https://www.amazon.com/s?k=standing+desk" ] }' | apify call om_kh/vigia-amazon-keyword-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=om_kh/vigia-amazon-keyword-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Search Monitor — New Product Alerts (Vigia)", "description": "Monitor an Amazon search or category and get only NEW products since last check, with an entrant-velocity spike signal. Catch new competitors entering your niche. Charged only on new products, never per run. Ideal for e-commerce and market-intel agents.", "version": "0.1", "x-build-id": "tt3MRpiS69zA6Si5q" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/om_kh~vigia-amazon-keyword-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-om_kh-vigia-amazon-keyword-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/om_kh~vigia-amazon-keyword-monitor/runs": { "post": { "operationId": "runs-sync-om_kh-vigia-amazon-keyword-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/om_kh~vigia-amazon-keyword-monitor/run-sync": { "post": { "operationId": "run-sync-om_kh-vigia-amazon-keyword-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "maxTotalChargeUsd" ], "properties": { "searchUrls": { "title": "Amazon search/category URLs", "type": "array", "description": "Amazon search or category URLs to monitor for new products.", "default": [], "items": { "type": "string" } }, "currentItems": { "title": "Bring your own items (optional)", "type": "array", "description": "Skip the chained fetch and pass records directly (no upstream call, no fetch fee).", "default": [] }, "maxTotalChargeUsd": { "title": "Maximum Vigia charge (USD)", "minimum": 0, "type": "number", "description": "Hard maximum amount that this run may charge.", "default": 1 }, "sources": { "title": "Declared upstream sources and estimated costs", "type": "array", "description": "Declare every upstream source before this run. Each item needs name, authorization, and estimated_cost_usd.", "default": [ { "name": "Chained upstream actor", "authorization": "public_structured_data", "estimated_cost_usd": 0 } ] }, "monitorEnabled": { "title": "Monitor only new results", "type": "boolean", "description": "The first monitored run stores a free baseline. Later runs deliver and charge only new results.", "default": false }, "monitorId": { "title": "Monitor ID (optional)", "type": "string", "description": "Pins the persistent baseline to a name of your choice, so separate targets never share state. Leave empty to derive it automatically.", "default": "" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```