# YouTube Search Monitor — New Video Alerts (Vigia) (`om_kh/vigia-youtube-search-monitor`) Actor Monitor a YouTube search term and get only NEW videos since last check, with an upload-velocity spike signal. Charged only on new videos, never per run. Ideal for brand-monitoring, trend-tracking and content-intel agents. - **URL**: https://apify.com/om\_kh/vigia-youtube-search-monitor.md - **Developed by:** [omar khandji](https://apify.com/om_kh) (community) - **Categories:** Social media, 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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 ## YouTube Search Monitor — New Video Alerts (Vigia) > Monitor a YouTube search term and get only NEW videos since last check, with an upload-velocity spike signal. Charged only on new videos, never per run. Ideal for brand-monitoring, trend-tracking and content-intel agents. ### What it does Track a keyword on YouTube and get only newly-uploaded videos, with an upload spike alert. 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. **You pay the alert price only for real change.** New-video alerts are billed only for genuinely new videos since your last check. A quiet run bills just the small source-check fee (the cost of looking) — never the alert price on unchanged data. Raw scrapers bill every row of a full re-scan every run. 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 { "searchTerms": [ "your brand", "competitor name" ], "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 - **Video alert** — billed once per new video since the last check (this is the only charge that scales with change). - **Source check** ($0.10) — billed once per monitored target per run, **only when the source responded**. A failed source is free. - **A quiet run bills only the source check** ($0.10), never the alert price. 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 ## `searchTerms` (type: `array`): Keywords/phrases to monitor on YouTube search. Each term is tracked independently for new uploads. ## `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 { "searchTerms": [ "your brand", "competitor name" ], "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 = { "searchTerms": [ "your brand", "competitor name" ] }; // Run the Actor and wait for it to finish const run = await client.actor("om_kh/vigia-youtube-search-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 = { "searchTerms": [ "your brand", "competitor name", ] } # Run the Actor and wait for it to finish run = client.actor("om_kh/vigia-youtube-search-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 '{ "searchTerms": [ "your brand", "competitor name" ] }' | apify call om_kh/vigia-youtube-search-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=om_kh/vigia-youtube-search-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Search Monitor — New Video Alerts (Vigia)", "description": "Monitor a YouTube search term and get only NEW videos since last check, with an upload-velocity spike signal. Charged only on new videos, never per run. Ideal for brand-monitoring, trend-tracking and content-intel agents.", "version": "0.1", "x-build-id": "kbW5BHJ1XE14I5Wwe" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/om_kh~vigia-youtube-search-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-om_kh-vigia-youtube-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/om_kh~vigia-youtube-search-monitor/runs": { "post": { "operationId": "runs-sync-om_kh-vigia-youtube-search-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/om_kh~vigia-youtube-search-monitor/run-sync": { "post": { "operationId": "run-sync-om_kh-vigia-youtube-search-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerms": { "title": "YouTube search terms", "type": "array", "description": "Keywords/phrases to monitor on YouTube search. Each term is tracked independently for new uploads.", "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 } } } } } } } } } } ```