MetaTrader5 MCP Server

from typing import Any, Dict, Optional, List from .schema import TimeframeLiteral, IndicatorSpec, DenoiseSpec, SimplifySpec from .server import mcp, _auto_connect_wrapper from ..services.data_service import fetch_candles, fetch_ticks # Explicitly define what should be exported for '*' imports __all__ = ['data_fetch_candles', 'data_fetch_ticks'] @mcp.tool() @_auto_connect_wrapper def data_fetch_candles( symbol: str, timeframe: TimeframeLiteral = "H1", limit: int = 10, start: Optional[str] = None, end: Optional[str] = None, ohlcv: Optional[str] = None, indicators: Optional[List[IndicatorSpec]] = None, denoise: Optional[DenoiseSpec] = None, simplify: Optional[SimplifySpec] = None, ) -> Dict[str, Any]: """Fetch historical candle data with optional technical indicators and denoising. **REQUIRED**: symbol parameter must be provided (e.g., "EURUSD", "BTCUSD") Features: --------- - OHLCV data in CSV format - Technical indicators (RSI, MACD, EMA, SMA, etc.) - Data denoising and smoothing - Data simplification for large datasets - Includes metadata: last_candle_open (true if last candle is still forming) Parameters: ----------- symbol : str (REQUIRED) Trading symbol (e.g., "EURUSD", "GBPUSD", "BTCUSD") timeframe : str, optional (default="H1") Candle timeframe: "M1", "M5", "M15", "M30", "H1", "H4", "D1", "W1", "MN1" limit : int, optional (default=10) Maximum number of candles to return start : str, optional Start date (e.g., "2025-08-29", "yesterday 14:00", "2 days ago") end : str, optional End date (same formats as start) ohlcv : str, optional Fields to include: "close", "ohlc", "ohlcv", "all" indicators : list, optional Technical indicators list, e.g., [{"name": "rsi", "params": [14]}] Or compact string: "rsi(14),ema(20),macd(12,26,9)" denoise : dict, optional Denoising configuration to smooth price data simplify : dict, optional Data reduction options for large datasets Returns: -------- dict - success: bool - symbol: str - timeframe: str - candles: int (number of candles returned) - last_candle_open: bool (true if last candle is still forming) - csv: str (CSV formatted candle data) Examples: --------- # Get last 10 H1 candles data_fetch_candles(symbol="EURUSD") # Get 100 M15 candles with RSI indicator data_fetch_candles( symbol="EURUSD", timeframe="M15", limit=100, indicators="rsi(14)" ) # Get date range with multiple indicators data_fetch_candles( symbol="GBPUSD", start="2025-11-01", end="2025-11-30", indicators="rsi(14),ema(20),macd(12,26,9)" ) """ return fetch_candles( symbol=symbol, timeframe=timeframe, limit=limit, start=start, end=end, ohlcv=ohlcv, indicators=indicators, denoise=denoise, simplify=simplify ) @mcp.tool() @_auto_connect_wrapper def data_fetch_ticks( symbol: str, limit: int = 100, start: Optional[str] = None, end: Optional[str] = None, simplify: Optional[SimplifySpec] = None, ) -> Dict[str, Any]: """Return latest ticks as CSV with columns: time,bid,ask and optional last,volume,flags. Parameters: symbol, limit, start?, end?, simplify? - `limit` limits the number of rows. - `start` starts from a flexible date/time; optional `end` enables range. - `simplify`: Optional dict to reduce or aggregate rows (select/approximate/resample). """ return fetch_ticks( symbol=symbol, limit=limit, start=start, end=end, simplify=simplify )