# GitHub Issues & PR Monitor (`lovely_radiologist/github-issues-monitor`) Actor Watch any GitHub repo or org for new issues and PRs matching label/keyword filters. Built for OSS maintainers, support teams, and competitive intelligence. Pairs naturally with Apify scheduler and webhooks. - **URL**: https://apify.com/lovely\_radiologist/github-issues-monitor.md - **Developed by:** [Vivek Gaur](https://apify.com/lovely_radiologist) (community) - **Categories:** Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 issue scrapeds 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.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 ## GitHub Issues & PR Monitor Watch any GitHub repo for new issues and pull requests matching **label and keyword filters** — built for automation and webhooks, not just one-off exports. ### Typical Use Cases - **OSS maintainers**: get notified when `bug` or `critical` issues appear - **Support teams**: watch for customer-reported issues across your org's repos - **Competitive intel**: monitor a competitor's OSS repo for feature requests - **AI agents**: scheduled run every hour → webhook → Slack/email alert pipeline ### Schedule This Actor This Actor is designed to run on a schedule. Set up in Apify Console: 1. Create a **Schedule** → run this Actor every hour 2. Add a **Webhook** on the run to POST results to your Slack/email endpoint 3. Use the `since` field (ISO date) to only fetch issues newer than your last run ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `repo` | string | — | `owner/repo` or GitHub URL | | `labels` | string[] | — | Filter by labels (OR logic) | | `keywords` | string[] | — | Filter by title/body keywords | | `since` | ISO date | — | Only return items after this date | | `state` | string | `open` | `open`, `closed`, or `all` | | `maxResults` | integer | 100 | Max items to return | ### Output ```json { "number": 1234, "title": "Memory leak in useEffect cleanup", "type": "issue", "author": "octocat", "labels": ["bug", "memory"], "state": "open", "url": "https://github.com/vercel/next.js/issues/1234", "createdAt": "2026-07-11T10:00:00Z", "bodyExcerpt": "When using useEffect with...", "repo": "vercel/next.js" } ```` ### Pricing (PPE) | Event | Price | |-------|-------| | `actor-start` | $0.01 | | `issue-found` | $0.01 per issue/PR | ### Related Actors - [GitHub Repository Insights](https://apify.com/TODO) — get the full repo health picture - [GitHub Org Scraper](https://apify.com/TODO) — monitor all repos in an org # Actor input Schema ## `repo` (type: `string`): Repository to monitor. Format: 'owner/repo' or a GitHub URL. ## `labels` (type: `array`): Only return issues/PRs with at least one of these labels. ## `keywords` (type: `array`): Only return issues/PRs whose title or body contains at least one of these keywords. ## `since` (type: `string`): Only return issues/PRs created or updated after this date. ISO 8601 format. ## `includesPRs` (type: `boolean`): Include pull requests in the results (GitHub API returns both issues and PRs unless filtered). ## `state` (type: `string`): Filter issues and PRs by their state: open, closed, or all. ## `maxResults` (type: `integer`): Maximum number of issues/PRs to return. ## Actor input object example ```json { "repo": "vercel/next.js", "labels": [ "bug", "feature-request" ], "keywords": [], "includesPRs": true, "state": "open", "maxResults": 100 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "repo": "vercel/next.js", "labels": [ "bug", "feature-request" ], "keywords": [], "since": "" }; // Run the Actor and wait for it to finish const run = await client.actor("lovely_radiologist/github-issues-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "repo": "vercel/next.js", "labels": [ "bug", "feature-request", ], "keywords": [], "since": "", } # Run the Actor and wait for it to finish run = client.actor("lovely_radiologist/github-issues-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 '{ "repo": "vercel/next.js", "labels": [ "bug", "feature-request" ], "keywords": [], "since": "" }' | apify call lovely_radiologist/github-issues-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lovely_radiologist/github-issues-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Issues & PR Monitor", "description": "Watch any GitHub repo or org for new issues and PRs matching label/keyword filters. Built for OSS maintainers, support teams, and competitive intelligence. Pairs naturally with Apify scheduler and webhooks.", "version": "0.1", "x-build-id": "Cws3MkrXARCg1J9y0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lovely_radiologist~github-issues-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lovely_radiologist-github-issues-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lovely_radiologist~github-issues-monitor/runs": { "post": { "operationId": "runs-sync-lovely_radiologist-github-issues-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lovely_radiologist~github-issues-monitor/run-sync": { "post": { "operationId": "run-sync-lovely_radiologist-github-issues-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "repo" ], "properties": { "repo": { "title": "Repository", "type": "string", "description": "Repository to monitor. Format: 'owner/repo' or a GitHub URL." }, "labels": { "title": "Label Filters", "type": "array", "description": "Only return issues/PRs with at least one of these labels.", "items": { "type": "string" } }, "keywords": { "title": "Keyword Filters", "type": "array", "description": "Only return issues/PRs whose title or body contains at least one of these keywords.", "items": { "type": "string" } }, "since": { "title": "Since (ISO date)", "type": "string", "description": "Only return issues/PRs created or updated after this date. ISO 8601 format." }, "includesPRs": { "title": "Include Pull Requests", "type": "boolean", "description": "Include pull requests in the results (GitHub API returns both issues and PRs unless filtered).", "default": true }, "state": { "title": "State", "enum": [ "open", "closed", "all" ], "type": "string", "description": "Filter issues and PRs by their state: open, closed, or all.", "default": "open" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of issues/PRs to return.", "default": 100 } } }, "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 } } } } } } } } } } ```