# Monitoring Checker Schema (`apify/monitoring-checker-schema`) Actor The monitoring checker schema is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this. - **URL**: https://apify.com/apify/monitoring-checker-schema.md - **Developed by:** [Apify](https://apify.com/apify) (Apify) - **Categories:** Developer tools - **Stats:** 41 total users, 5 monthly users, 100.0% runs succeeded, 8 bookmarks - **User rating**: 4.80 out of 5 stars ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Monitoring checker schema This actor is a part of Apify Monitoring Suite [apify/monitoring](https://apify.com/apify/monitoring). This checker checks if the resource meets the limitation provided in the input. Also checks if the resource items structure matches the provided schema. # Actor input Schema ## `options` (type: `string`): List of validation options selected by list of dataset IDs or by the regular expression. It is possible to define minimum item count, maximum item count and validation schema (type-check) for each defined validation options. ## `subjectType` (type: `string`): Type of the resource to checked. ## `name` (type: `string`): Name of actor, task or dataset to be checked. ## `id` (type: `string`): Id of actor, task or dataset to be checked. ## `runs` (type: `array`): List of specific actor or task runs. ## Actor input object example ```json { "options": "/* global t */\n// t variable definition because of type validation ... \n [{\n schema: {\n url: t.string.url,\n date: t.string.date,\n messages: t.array,\n },\n}, \n{\n filter: 'eshop', // you can also use IDs definition as: Ids: [\"id\", \"id\"]\n minItemCount: 100, \n maxItemCount: 1000\n}]", "subjectType": "ACTOR", "runs": [] } ```` # 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 = { "options": `/* global t */ // t variable definition because of type validation ... [{ schema: { url: t.string.url, date: t.string.date, messages: t.array, }, }, { filter: 'eshop', // you can also use IDs definition as: Ids: ["id", "id"] minItemCount: 100, maxItemCount: 1000 }]` }; // Run the Actor and wait for it to finish const run = await client.actor("apify/monitoring-checker-schema").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 = { "options": """/* global t */ // t variable definition because of type validation ... [{ schema: { url: t.string.url, date: t.string.date, messages: t.array, }, }, { filter: 'eshop', // you can also use IDs definition as: Ids: [\"id\", \"id\"] minItemCount: 100, maxItemCount: 1000 }]""" } # Run the Actor and wait for it to finish run = client.actor("apify/monitoring-checker-schema").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 '{ "options": "/* global t */\\n// t variable definition because of type validation ... \\n [{\\n schema: {\\n url: t.string.url,\\n date: t.string.date,\\n messages: t.array,\\n },\\n}, \\n{\\n filter: '\''eshop'\'', // you can also use IDs definition as: Ids: [\\"id\\", \\"id\\"]\\n minItemCount: 100, \\n maxItemCount: 1000\\n}]" }' | apify call apify/monitoring-checker-schema --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apify/monitoring-checker-schema", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Monitoring Checker Schema", "description": "The monitoring checker schema is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.", "version": "0.0", "x-build-id": "pfHL9xDXimiEDabq0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apify~monitoring-checker-schema/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apify-monitoring-checker-schema", "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/apify~monitoring-checker-schema/runs": { "post": { "operationId": "runs-sync-apify-monitoring-checker-schema", "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/apify~monitoring-checker-schema/run-sync": { "post": { "operationId": "run-sync-apify-monitoring-checker-schema", "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": [ "options", "subjectType", "name", "id" ], "properties": { "options": { "title": "Validation options", "type": "string", "description": "List of validation options selected by list of dataset IDs or by the regular expression. It is possible to define minimum item count, maximum item count and validation schema (type-check) for each defined validation options." }, "subjectType": { "title": "Subject type", "enum": [ "ACTOR", "TASK", "NAMED_DATASET" ], "type": "string", "description": "Type of the resource to checked.", "default": "ACTOR" }, "name": { "title": "Subject name", "type": "string", "description": "Name of actor, task or dataset to be checked." }, "id": { "title": "Subject id", "type": "string", "description": "Id of actor, task or dataset to be checked." }, "runs": { "title": "List of runs", "type": "array", "description": "List of specific actor or task runs.", "default": [], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```