# AlphaSignal — Crypto Futures Screener (`ayrtondavoli97/kucoin-scraper`) Actor Advanced multi-timeframe screener for crypto perpetual futures. Generates LONG/SHORT signals with 7-signal confluence scoring, ATR-based TP/SL, support/resistance levels and market structure. No API keys needed. - **URL**: https://apify.com/ayrtondavoli97/kucoin-scraper.md - **Developed by:** [Francesco Ayrton Davoli](https://apify.com/ayrtondavoli97) (community) - **Categories:** AI, Automation, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.00 / 1,000 results 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 ## AlphaSignal — Crypto Futures Screener **Advanced multi-timeframe technical screener for crypto perpetual futures.** Screens all active USDT-margined pairs, runs a 7-signal confluence engine across two timeframes, and outputs structured datasets with directional signals, ATR-calibrated TP/SL levels, support & resistance zones, and market structure classification. No API keys required. Currently supports: **KuCoin Futures** (Binance/Bybit coming soon). --- ### What makes this different | Feature | AlphaSignal | Typical screener | |---------|-------------|-----------------| | Multi-timeframe confluence (1h + 4h) | ✓ | ✗ | | ATR-based TP/SL (not fixed %) | ✓ | ✗ | | Risk/reward ratio per signal | ✓ | ✗ | | Stochastic RSI | ✓ | ✗ | | 7-signal confluence count | ✓ | ✗ | | Support & resistance levels | ✓ | ✗ | | Market structure (HH/HL/LH/LL) | ✓ | ✗ | | VWAP position filter | ✓ | ✗ | | Volume spike detection | ✓ | ✗ | | Signal age (candles since formed) | ✓ | ✗ | | EMA 200 macro filter | ✓ | ✗ | --- ### Example output ```json { "symbol": "XAGUSDTM", "direction": "SHORT", "confidence": 0.99, "confluence_count": 6, "htf_direction": "SHORT", "mtf_aligned": true, "trade_quality_score": 85.5, "tradeable": true, "market_regime": "TRENDING_BEAR", "market_structure": "BEARISH", "entry_zone": { "low": 71.82, "high": 72.19 }, "take_profit": 69.96, "stop_loss": 73.24, "risk_reward_ratio": 1.67, "support_levels": [70.1, 68.4, 67.2], "resistance_levels": [73.5, 74.8], "signal_age_candles": 2, "volume_spike": false, "analysis_summary": "XAGUSDTM SHORT | HTF:SHORT | conf 99% | confluence 6/7 | regime TRENDING_BEAR | R:R 1.67 | setup acceptable" } ```` *** ### How signals work Each symbol is evaluated against **7 independent signals**: | Signal | Long condition | Short condition | |--------|---------------|----------------| | EMA stack 9/21/50 | 9 > 21 > 50 | 9 < 21 < 50 | | MACD histogram | hist > 0 | hist < 0 | | RSI 14 | ≥ 58 | ≤ 42 | | Stochastic RSI | K > 50, K > D | K < 50, K < D | | Bollinger position | pos ≥ 0.65 | pos ≤ 0.35 | | VWAP position | price > VWAP | price < VWAP | | Volume spike | confirms direction | confirms direction | `confluence_count` tells you how many of 7 agree. A signal with 6/7 is far stronger than 3/7. #### Multi-timeframe confirmation With `enableMtf: true` (default), the full engine also runs on 4h. When both agree: `mtf_aligned: true` and +5 bonus on quality score. Use `includeOnlyMtfAligned: true` for high-conviction setups only. #### ATR-based TP/SL ``` take_profit = price + (ATR × tpAtrMult) ## default ×2.5 stop_loss = price − (ATR × slAtrMult) ## default ×1.5 ``` Levels adapt to actual market volatility — no fixed percentages. Multipliers are configurable. *** ### Output fields | Field | Description | |-------|-------------| | `symbol` | Futures symbol | | `direction` | LONG / SHORT / NEUTRAL | | `confidence` | 0–1, weight on winning direction | | `confluence_count` | Signals agreeing (0–7) | | `htf_direction` | Higher timeframe direction | | `mtf_aligned` | True if both timeframes agree | | `trade_quality_score` | Composite 0–100 quality score | | `tradeable` | True if all checks pass | | `tradeable_reason` | Why tradeable or not | | `risk_level` | LOW / MEDIUM / HIGH | | `market_regime` | TRENDING\_BULL/BEAR, RANGING, VOLATILE | | `market_structure` | BULLISH / BEARISH / RANGING | | `entry_zone` | {low, high} near current price | | `take_profit` | ATR-based target level | | `stop_loss` | ATR-based stop level | | `risk_reward_ratio` | reward / risk | | `support_levels` | Up to 3 swing lows below price | | `resistance_levels` | Up to 3 swing highs above price | | `signal_age_candles` | Candles since current direction formed | | `volume_spike` | True if volume ≥ 2× 20-period average | | `funding_rate` | Current perpetual funding rate | *** ### Input parameters | Parameter | Default | Description | |-----------|---------|-------------| | `timeframe` | 1hour | Primary candle granularity | | `enableMtf` | true | Multi-timeframe confluence | | `htfTimeframe` | 4hour | Higher timeframe | | `maxSymbols` | 120 | Max symbols by 24h volume | | `min24hVolumeUsd` | 1,000,000 | Minimum liquidity filter | | `directionFilter` | — | LONG / SHORT / blank for all | | `tpAtrMult` | 2.5 | Take profit ATR multiplier | | `slAtrMult` | 1.5 | Stop loss ATR multiplier | | `includeOnlyTradeable` | false | Only tradeable setups | | `includeOnlyMtfAligned` | false | Only MTF-confirmed setups | | `symbolFilter` | — | Whitelist specific symbols | | `excludeSymbols` | — | Blacklist symbols | *** ### Use cases - **Signal generation** — Feed `tradeable: true, mtf_aligned: true` into your execution bot - **Watchlist building** — Run daily, filter `confluence_count >= 5` - **Market scanning** — Monitor `market_structure` across all futures - **Backtesting prep** — Full dataset with `includeRawCandles: true` - **Scheduled alerts** — Apify schedules + webhooks for hourly updates *** ### Performance - 120 symbols analyzed in ~2.5 minutes - No API keys or authentication required - \~$0.02 per full run at default settings *** ### Changelog **v2.0** — Multi-timeframe confluence, StochRSI, VWAP, ATR TP/SL, R:R ratio, support/resistance levels, market structure, signal age, volume spike, EMA 200, confluence count, fixed ADX bonus logic, configurable TP/SL multipliers. **v1.0** — Initial release. *** *AlphaSignal is for market analysis only. It does not execute live trades. Always apply your own risk management before acting on any signal.* # Actor input Schema ## `symbolFilter` (type: `array`): Optional. If provided, only these KuCoin futures symbols are analyzed (e.g. BTCUSDTM, ETHUSDTM). ## `excludeSymbols` (type: `array`): Symbols to skip entirely. ## `timeframe` (type: `string`): Candle granularity for the main analysis. ## `enableMtf` (type: `boolean`): Fetch a higher timeframe and check directional alignment. Adds mtf\_aligned and htf\_direction fields. ## `htfTimeframe` (type: `string`): The higher timeframe used for confluence confirmation. ## `bars` (type: `integer`): Number of historical candles to download. Minimum 80, recommended 220+. ## `maxSymbols` (type: `integer`): Top N symbols by 24h volume. ## `min24hVolumeUsd` (type: `integer`): Filter out illiquid pairs below this threshold. ## `directionFilter` (type: `string`): Return only LONG signals, only SHORT signals, or all (leave blank). ## `tpAtrMult` (type: `number`): Take profit = price +/- (ATR x this value). Default 2.5. ## `slAtrMult` (type: `number`): Stop loss = price +/- (ATR x this value). Default 1.5. ## `includeOnlyTradeable` (type: `boolean`): If enabled, only return symbols that pass all tradeability checks. ## `includeOnlyMtfAligned` (type: `boolean`): If enabled, only return symbols where primary and higher timeframe directions agree. ## `includeRawCandles` (type: `boolean`): Attach the last 5 OHLCV candles to each result. ## `datasetSortBy` (type: `string`): Field used to rank the final output. ## Actor input object example ```json { "excludeSymbols": [], "timeframe": "1hour", "enableMtf": true, "htfTimeframe": "4hour", "bars": 220, "maxSymbols": 120, "min24hVolumeUsd": 1000000, "directionFilter": "", "tpAtrMult": 2.5, "slAtrMult": 1.5, "includeOnlyTradeable": false, "includeOnlyMtfAligned": false, "includeRawCandles": false, "datasetSortBy": "trade_quality_score" } ``` # 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("ayrtondavoli97/kucoin-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 = {} # Run the Actor and wait for it to finish run = client.actor("ayrtondavoli97/kucoin-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 '{}' | apify call ayrtondavoli97/kucoin-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ayrtondavoli97/kucoin-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AlphaSignal — Crypto Futures Screener", "description": "Advanced multi-timeframe screener for crypto perpetual futures. Generates LONG/SHORT signals with 7-signal confluence scoring, ATR-based TP/SL, support/resistance levels and market structure. No API keys needed.", "version": "0.0", "x-build-id": "UhFxGTS1di28Zd56x" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ayrtondavoli97~kucoin-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ayrtondavoli97-kucoin-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ayrtondavoli97~kucoin-scraper/runs": { "post": { "operationId": "runs-sync-ayrtondavoli97-kucoin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ayrtondavoli97~kucoin-scraper/run-sync": { "post": { "operationId": "run-sync-ayrtondavoli97-kucoin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "symbolFilter": { "title": "Symbol whitelist", "type": "array", "description": "Optional. If provided, only these KuCoin futures symbols are analyzed (e.g. BTCUSDTM, ETHUSDTM).", "items": { "type": "string" } }, "excludeSymbols": { "title": "Symbol blacklist", "type": "array", "description": "Symbols to skip entirely.", "items": { "type": "string" }, "default": [] }, "timeframe": { "title": "Primary timeframe", "enum": [ "1min", "5min", "15min", "30min", "1hour", "4hour", "1day" ], "type": "string", "description": "Candle granularity for the main analysis.", "default": "1hour" }, "enableMtf": { "title": "Enable multi-timeframe analysis", "type": "boolean", "description": "Fetch a higher timeframe and check directional alignment. Adds mtf_aligned and htf_direction fields.", "default": true }, "htfTimeframe": { "title": "Higher timeframe (MTF)", "enum": [ "15min", "30min", "1hour", "4hour", "1day" ], "type": "string", "description": "The higher timeframe used for confluence confirmation.", "default": "4hour" }, "bars": { "title": "Candle count", "minimum": 80, "maximum": 500, "type": "integer", "description": "Number of historical candles to download. Minimum 80, recommended 220+.", "default": 220 }, "maxSymbols": { "title": "Max symbols to analyze", "minimum": 1, "maximum": 500, "type": "integer", "description": "Top N symbols by 24h volume.", "default": 120 }, "min24hVolumeUsd": { "title": "Min 24h volume (USD)", "type": "integer", "description": "Filter out illiquid pairs below this threshold.", "default": 1000000 }, "directionFilter": { "title": "Direction filter", "enum": [ "", "LONG", "SHORT" ], "type": "string", "description": "Return only LONG signals, only SHORT signals, or all (leave blank).", "default": "" }, "tpAtrMult": { "title": "Take profit ATR multiplier", "minimum": 0.5, "maximum": 10, "type": "number", "description": "Take profit = price +/- (ATR x this value). Default 2.5.", "default": 2.5 }, "slAtrMult": { "title": "Stop loss ATR multiplier", "minimum": 0.3, "maximum": 5, "type": "number", "description": "Stop loss = price +/- (ATR x this value). Default 1.5.", "default": 1.5 }, "includeOnlyTradeable": { "title": "Tradeable setups only", "type": "boolean", "description": "If enabled, only return symbols that pass all tradeability checks.", "default": false }, "includeOnlyMtfAligned": { "title": "MTF-aligned setups only", "type": "boolean", "description": "If enabled, only return symbols where primary and higher timeframe directions agree.", "default": false }, "includeRawCandles": { "title": "Include last 5 raw candles", "type": "boolean", "description": "Attach the last 5 OHLCV candles to each result.", "default": false }, "datasetSortBy": { "title": "Sort dataset by", "enum": [ "trade_quality_score", "confidence", "confluence_score", "liquidity_score", "symbol" ], "type": "string", "description": "Field used to rank the final output.", "default": "trade_quality_score" } } }, "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 } } } } } } } } } } ```