History of MQL5.community development

In this article, we will see that not everything always needs to be implemented in a certain specific way. There are alternative approaches to problem-solving. To properly understand this article, it is necessary to grasp the concepts described in the previous articles. The materials presented here are for educational purposes only. They should not be considered as a final application, the goal of which is not to study the concepts presented here.

Learn how to add “Sign in with MQL5” to your Android app using the OAuth 2.0 authorization code flow. The guide covers app registration, endpoints, redirect URI, Custom Tabs, deep-link handling, and a PHP backend that exchanges the code for an access token over HTTPS. You will authenticate real MQL5 users and access profile data such as rank and reputation.

Build a non‑repainting Supertrend in MQL5 for MetaTrader 5 from first principles. We use an iATR handle and CopyBuffer for volatility, bind buffers with SetIndexBuffer, and configure plots (DRAWCOLORCANDLES plus two line bands) via PlotIndexSetInteger. The logic updates only on closed bars with EMPTY_VALUE to suppress inactive bands, exposing atrPeriod and atrMultiplier inputs. You get a clean, EA‑ready overlay with documented buffers for strategies and signals.

We are creating an adaptive self-learning trading expert advisor based on DQN machine learning, with multidimensional causal inference. The EA will successfully trade simultaneously on 7 currency pairs. And agents of different pairs will exchange information with each other.

Liquidity zones are commonly traded by waiting for the price to return and retest the zone of interest, often through the placement of pending orders within these areas. In this article, we leverage MQL5 to bring this concept to life, demonstrating how such zones can be identified programmatically and how risk management can be systematically applied. Join the discussion as we explore both the logic behind liquidity-based trading and its practical implementation.

Building on the previous article that introduced the market state classification module, this installment focuses on implementing the core logic for identifying and evaluating compression zones. It presents a range contraction detection and maturity grading system in MQL5 that analyzes market congestion using price action alone.

Create a practical bridge between MetaTrader 5 and Binance: fetch 30‑minute klines with WebRequest, extract OHLC/time values from JSON, and confirm a bullish engulfing pattern using only completed candles. Then assemble the query string, compute the HMAC‑SHA256 signature, add X‑MBX‑APIKEY, and submit authenticated orders. You get a clear, end‑to‑end EA workflow from data acquisition to order execution.

Do you want to know how to benefit from the difference in interest rates? This article considers how to use swap arbitrage in Forex to earn stable profit every night, creating a portfolio that is resistant to market fluctuations.