# KLSE Screener — Bursa Malaysia Listed Companies (`jungle_synthesizer/klse-screener-bursa-malaysia-listed-company-scraper`) Actor Scrape Bursa Malaysia listed companies via KLSE Screener. Three modes: full KLSE roster (P/E, dividend yield, ROE, EPS, NTA), per-company quarterly financials, and the live Bursa announcement stream. For retail-investor tooling, quant screeners and equity-research desks. No API key needed. - **URL**: https://apify.com/jungle\_synthesizer/klse-screener-bursa-malaysia-listed-company-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 70.0% runs succeeded, NaN 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.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 ## KLSE / Bursa Malaysia Listed Company Scraper Scrape the entire Bursa Malaysia (KLSE) listed-company universe. Returns the full Main / ACE / LEAP market roster with current prices and fundamentals, per-company deep financials, and the live company-announcement stream mirrored from Bursa LINK. ### What you get **Roster snapshot** — a single call returns ~1,139 rows covering every stock listed on Bursa Malaysia's three market boards: | Field | Description | |---|---| | `stock_code` | Bursa 4-digit code (e.g. `1155` = Maybank) | | `stock_name` | Ticker short name | | `company_full_name` | Full registered company name | | `market_board` | `MAIN` / `ACE` / `LEAP` | | `sector` | Bursa sector classification | | `last_price` | Last traded price (MYR) | | `price_change` / `price_change_pct` | Intraday movement | | `volume` | Traded volume | | `market_cap_rm` | Market capitalisation (MYR millions) | | `eps` | Earnings per share (sen) | | `pe_ratio` | Price/earnings ratio | | `dividend_yield_pct` | Dividend yield (%) | | `roe_pct` | Return on equity (%) | | `nta` | Net tangible assets per share | | `week_52_high` / `week_52_low` | 52-week range | **Company deep-dive** — per-company financials for specific stock codes: - Annual revenue and net profit history - 52-week price range, ROE, EPS, NTA, market cap, shares outstanding - Supply a list of stock codes or leave blank to derive from the roster **Announcement stream** — the live Bursa company-announcement feed, paginated: - Announcement title, category, company name, datetime - Categories: Financial Results, General Announcement, Changes in Corporate Info, etc. - Filter by category or scrape all ### Modes | Mode | Input | Description | |---|---|---| | `roster_snapshot` | — | Full ~1,139-company roster with fundamentals | | `company_deep` | `stockCodes` | Per-company financials for supplied codes | | `announcements` | `announcementCategories` | Live announcement stream (paginated) | ### Why KLSE Screener (not Bursa Malaysia official) The official `bursamalaysia.com` site is Cloudflare-challenged on every market-data path (verified 403 + "Just a moment" interstitial). KLSE Screener mirrors the same Bursa data without Cloudflare. The roster endpoint returns all listed companies in a single AJAX call (~2.9 MB) with complete fundamentals — no page-by-page pagination required. ### Input ```json { "mode": "roster_snapshot", "maxItems": 200, "stockCodes": ["1155", "1023"], "sectors": [], "announcementCategories": [], "sp_intended_usage": "Building a screener for MY retail investors", "sp_improvement_suggestions": "" } ```` #### Parameters | Parameter | Default | Description | |---|---|---| | `mode` | `roster_snapshot` | Which data to scrape | | `maxItems` | 200 | Maximum records to return | | `stockCodes` | `[]` | For `company_deep` mode: Bursa 4-digit codes. Empty = use roster | | `sectors` | `[]` | For `roster_snapshot`: filter by sector name. Empty = all sectors | | `announcementCategories` | `[]` | For `announcements`: filter by category. Empty = all | ### Output sample (roster\_snapshot) ```json { "record_type": "company", "stock_code": "1155", "stock_name": "MAYBANK", "company_full_name": "MALAYAN BANKING BERHAD", "market_board": "MAIN", "sector": "Banking", "sub_sector": "Financial Services", "last_price": 11.1, "price_change": 0.04, "price_change_pct": 0.36, "volume": 12340000, "market_cap_rm": 134300, "eps": 86.93, "pe_ratio": 12.77, "dividend_yield_pct": 5.68, "roe_pct": 11.24, "nta": 7.73, "week_52_high": 12.42, "week_52_low": 9.39, "source_url": "https://www.klsescreener.com/v2/screener/quote_results", "scraped_at": "2026-05-17T00:37:00.000Z" } ``` ### Use cases - **Quant screeners**: Pull the entire ~1,139-company universe with P/E, DY, ROE, EPS in one run — filter for value/dividend/growth criteria - **Retail investor tools**: Power a portfolio tracker or stock discovery app for the Malaysian market - **Research desks**: Monitor the Bursa announcement feed for material information, substantial-shareholding changes, and quarterly results - **Data pipelines**: Feed an automated screener or alerting system — run on a schedule, compare snapshots to detect price movement or new announcements ### Pricing Per-result pricing via Apify PPE. The roster snapshot fetches all ~1,139 companies in a single network call, making it exceptionally cost-efficient for full-universe pulls. ### Notes - No API key required - Datacenter proxy sufficient — KLSE Screener has no Cloudflare protection - Self-throttle applies (~1 req/2s for detail pages) to respect the site's AdSense-funded free model - Data is sourced from KLSE Screener which mirrors Bursa Malaysia's official listing; prices may lag real-time by minutes # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `mode` (type: `string`): roster\_snapshot: full KLSE roster with fundamentals in one call. company\_deep: per-company quarterly financials (uses stockCodes list or derives from roster). announcements: live Bursa announcement stream, paginated. ## `stockCodes` (type: `array`): Bursa 4-digit codes (e.g. 1155 = Maybank, 5347 = Tenaga). Leave empty in company\_deep mode to derive codes from the full roster. ## `sectors` (type: `array`): Filter roster by Bursa sector names (e.g. Technology, Finance). Empty = all sectors. ## `announcementCategories` (type: `array`): Filter by announcement category. Empty = all categories. ## `maxItems` (type: `integer`): Maximum number of records to return. Roster snapshot returns up to ~1,140 companies in one call. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "roster_snapshot", "stockCodes": [ "1155", "5347" ], "sectors": [], "announcementCategories": [], "maxItems": 15 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "roster_snapshot", "stockCodes": [ "1155", "5347" ], "sectors": [], "announcementCategories": [], "maxItems": 15 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/klse-screener-bursa-malaysia-listed-company-scraper").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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "roster_snapshot", "stockCodes": [ "1155", "5347", ], "sectors": [], "announcementCategories": [], "maxItems": 15, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/klse-screener-bursa-malaysia-listed-company-scraper").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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "roster_snapshot", "stockCodes": [ "1155", "5347" ], "sectors": [], "announcementCategories": [], "maxItems": 15 }' | apify call jungle_synthesizer/klse-screener-bursa-malaysia-listed-company-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/klse-screener-bursa-malaysia-listed-company-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "KLSE Screener — Bursa Malaysia Listed Companies", "description": "Scrape Bursa Malaysia listed companies via KLSE Screener. Three modes: full KLSE roster (P/E, dividend yield, ROE, EPS, NTA), per-company quarterly financials, and the live Bursa announcement stream. For retail-investor tooling, quant screeners and equity-research desks. No API key needed.", "version": "0.1", "x-build-id": "tgO8Jrq5GMy1LwcCx" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~klse-screener-bursa-malaysia-listed-company-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-klse-screener-bursa-malaysia-listed-company-scraper", "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/jungle_synthesizer~klse-screener-bursa-malaysia-listed-company-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-klse-screener-bursa-malaysia-listed-company-scraper", "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/jungle_synthesizer~klse-screener-bursa-malaysia-listed-company-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-klse-screener-bursa-malaysia-listed-company-scraper", "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": [ "sp_intended_usage", "sp_improvement_suggestions" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "mode": { "title": "Scrape Mode", "enum": [ "roster_snapshot", "company_deep", "announcements" ], "type": "string", "description": "roster_snapshot: full KLSE roster with fundamentals in one call. company_deep: per-company quarterly financials (uses stockCodes list or derives from roster). announcements: live Bursa announcement stream, paginated." }, "stockCodes": { "title": "Stock Codes (company_deep mode)", "type": "array", "description": "Bursa 4-digit codes (e.g. 1155 = Maybank, 5347 = Tenaga). Leave empty in company_deep mode to derive codes from the full roster.", "items": { "type": "string" } }, "sectors": { "title": "Sector Filter (roster_snapshot mode)", "type": "array", "description": "Filter roster by Bursa sector names (e.g. Technology, Finance). Empty = all sectors.", "items": { "type": "string" } }, "announcementCategories": { "title": "Announcement Categories (announcements mode)", "type": "array", "description": "Filter by announcement category. Empty = all categories.", "items": { "type": "string" } }, "maxItems": { "title": "Max Records", "type": "integer", "description": "Maximum number of records to return. Roster snapshot returns up to ~1,140 companies in one call.", "default": 15 } } }, "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 } } } } } } } } } } ```