# My Actors Issues Notifier πŸ”” (`azzouzana/my-actors-issues-notifier`) Actor Up your Apify game πŸ”₯ Get notified when users open/re-open issues on your Apify actors. This actor monitors your actors for new open/re-opened issues and automatically writes them to a JSON dataset, ready for external integrations (Telegram, Slack, Jira, n8n or custom webhooks..) - 100% Open Source - **URL**: https://apify.com/azzouzana/my-actors-issues-notifier.md - **Developed by:** [Azzouzana](https://apify.com/azzouzana) (community) - **Categories:** Automation, Developer tools, Open source - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## 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 ## πŸ”” My Actors Issues Notifier An **Open Source** actor that pulls your Apify Console for **new open**/**reopened** actor issues on your account and writes webhook-ready rows to the **default dataset** - connect [Telegram, Slack, and more](https://docs.apify.com/platform/integrations/webhooks) from Integrations. ### How it works 1. `POST /public/authentication/resume` β€” uses console `ApifyRT` cookie β†’ short-lived `uiToken` 2. Socket.IO subscribe to `userOwnedPublicActorsIssuesPub` (paginated) 3. Keeps issues with `status === "OPEN"` 4. Named KV store `apify-console-open-issues`: - `firstRunComplete` β€” `false` until the first successful poll finishes (To not detect already open issues while running this for the first time) - `seenIssueIds` β€” currently open issue IDs (closed IDs are removed each run) 5. **First run** (`firstRunComplete` unset): save open ids + set flag β€” **no** dataset push 6. **Later runs**: for each new open id, `GET /actor-issues/{issueId}/comments` (last array entry) β†’ dataset row (`type: "new_open_issue"`), then refresh `seenIssueIds` 7. On resume/socket errors: one dataset row (`type: "fetch_failure"`) ### Dataset records **New issue** (`type: "new_open_issue"`): | Field | Type | Description | |--------|------|-------------| | `type` | `string` | Always `"new_open_issue"` | | `notifiedAt` | `string` | ISO timestamp when the record was pushed | | `issueId` | `string` | Issue `_id` from Console | | `title` | `string` | Issue title | | `status` | `string` | Issue status (e.g. `"OPEN"`) | | `objectType` | `string` | e.g. `"PAID_ACTOR"` | | `objectId` | `string` | Linked object id (often same as actor `_id`) | | `createdAt` | `string` | Issue creation time (ISO) | | `url` | `string` | Direct link to the issue in Console | | `actorTitle` | `string` | Actor display title (fallback: actor name or `objectId`) | | `reporter` | `string` | Reporter display name or username | | `lastComment` | `string \| null` | Text of the last entry in `/actor-issues/{issueId}/comments` (HTML stripped) | Example dataset output: ```json [ { "type": "new_open_issue", "notifiedAt": "2026-06-02T10:33:00.204Z", "issueId": "12345678910", "title": "test an open issue", "status": "OPEN", "objectType": "PAID_ACTOR", "objectId": "987654321", "createdAt": "2026-06-02T10:26:17.375Z", "url": "https://console.apify.com/actors/VzKtdb1t0Qnc07X8V/issues/12345678910", "actorTitle": "SofaScore scraper PRO⚑", "reporter": "dumy_username", "lastComment": "This is an open issue with dummy run" } ] ```` **Failure** (`type: "fetch_failure"`): | Field | Description | |--------|-------------| | `step` | e.g. `authentication/resume`, `socket.io subscribe` | | `errorMessage` | Error detail | | `notifiedAt` | ISO timestamp | Each new or failed notification is a row in this actor’s **default dataset**. Use that for integrationsβ€”no extra code required in this repo. ### Configuration #### Actor input | Input | Required | Notes | |--------|----------|--------| | `apifyRt` | Yes | `ApifyRT` cookie from console.apify.com | Copy ApifyRT from DevTools β†’ **Application** β†’ **Cookies** β†’ `https://console.apify.com`. Create a **scheduled task** and set `apifyRt` in the task input so the actor runs on a interval (e.g. every 10–15 minutes). #### Webhooks (Telegram, Slack, etc.) Open the actor’s **Integrations** tab in Apify Console: There, you can connect your preferred communication app (Slack, Telegram, WhatsApp, etc.) or ticketing system (Jira, Trello, Linear, etc.) using either Apify's native integrations or custom webhooks. - Trigger on **actor run succeeded** - Point the integration at this actor’s **default dataset** and map fields such as `title`, `actorTitle`, `reporter`, and `url` etc in your custom message template. ### πŸ“¬ Contact & Support **Have feedback, a question, or just want to say hi?** We'd love to hear from you! - πŸ’¬ **Discord**: `@azzouzana` - πŸ“§ **Email**: ***
Made with ❀️ for the data community.
# Actor input Schema ## `apifyRt` (type: `string`): Console session cookie (DevTools β†’ Application β†’ Cookie β†’ console.apify.com). ## Actor input object example ```json {} ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("azzouzana/my-actors-issues-notifier").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = {} # Run the Actor and wait for it to finish run = client.actor("azzouzana/my-actors-issues-notifier").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call azzouzana/my-actors-issues-notifier --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=azzouzana/my-actors-issues-notifier", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "My Actors Issues Notifier πŸ””", "description": "Up your Apify game πŸ”₯ Get notified when users open/re-open issues on your Apify actors. This actor monitors your actors for new open/re-opened issues and automatically writes them to a JSON dataset, ready for external integrations (Telegram, Slack, Jira, n8n or custom webhooks..) - 100% Open Source", "version": "0.0", "x-build-id": "dBWzrIhRNU5lmb4mv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/azzouzana~my-actors-issues-notifier/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-azzouzana-my-actors-issues-notifier", "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/azzouzana~my-actors-issues-notifier/runs": { "post": { "operationId": "runs-sync-azzouzana-my-actors-issues-notifier", "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/azzouzana~my-actors-issues-notifier/run-sync": { "post": { "operationId": "run-sync-azzouzana-my-actors-issues-notifier", "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": [ "apifyRt" ], "properties": { "apifyRt": { "title": "ApifyRT cookie", "type": "string", "description": "Console session cookie (DevTools β†’ Application β†’ Cookie β†’ console.apify.com)." } } }, "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 } } } } } } } } } } ```