Multi-Timeframe TradingView to MT5 Automation System via Python
A custom multi-timeframe trading signal and execution system that connects TradingView alerts with Python and MetaTrader 5 (MT5) — aggregating 4H and 1H indicator signals, evaluating confluence bias, and automatically routing qualifying trades to MT5 for instant execution with a live monitoring dashboard.
The challenge
Executing complex multi-timeframe TradingView indicator alerts directly in MT5 is impossible natively — traders need a centralized middleware layer to aggregate signals, calculate confluence bias, and dispatch orders automatically across multiple instruments without delay or missed triggers.
Key Project Constraints & Requirements
Multi-Timeframe Webhook Ingestion
Ingests real-time alert payloads across 4H and 1H timeframes from multiple TradingView chart indicators with sub-millisecond queuing.
Big Arrow & Small Arrow Confluence
Combines macro trend confirmation (Big Arrow) with micro entry triggers (Small Arrow) to calculate deterministic BUY/SELL bias.
Multi-Asset Portfolio Routing
Monitors and executes trades across Gold, Silver, US500, US Oil, BTCUSD, EURUSD, TSLA, NVDA simultaneously.
Real-Time Telemetry & Event Logging
Provides a live visual dashboard displaying incoming webhook states, current bias scores, and timestamped MT5 execution receipts.
Zero-Latency MT5 API Bridge
Connects directly to the MetaTrader 5 terminal using high-performance Python socket bridges for automated position dispatch.
The solution
A Python-based signal aggregation and execution engine connected to TradingView via webhooks. The system ingests incoming alerts across multiple timeframes (4H & 1H), combines Big Arrow and Small Arrow signals to evaluate overall BUY/SELL market bias, and displays real-time signal states and event logs on a live dashboard. When confluence conditions are satisfied, Python automatically routes qualifying orders directly to MetaTrader 5 for instant execution across multi-asset portfolios.
High-Throughput Webhook Listener
Asynchronous Python FastAPI service that authenticates, deserializes, and queues incoming TradingView JSON alert webhooks.
Multi-Timeframe Confluence Engine
Evaluates 4H higher-timeframe trend directional bias against 1H entry triggers (Big/Small arrows) to prevent trading against the macro trend.
Automated MT5 Execution Pipeline
Translates validated signal confluence into parameterized MT5 market and limit orders with automated stop loss and take profit calculation.
Real-Time Monitoring Dashboard
Web-based status console featuring multi-symbol signal matrices, live confluence indicators, and granular webhook debugging logs.
Technical architecture
A comprehensive breakdown of the TradingView webhook pipeline, Python confluence engine, and MetaTrader 5 live order execution architecture.
Verified outcome
TradingView alerts across 4H and 1H timeframes are converted into consolidated market bias and executed automatically in MT5 with sub-second latency.
Looking for a different platform?
We engineer production automated trading systems across all major retail and institutional environments.
Ready to automate your TradingView strategies to MT5?
Whether you need custom Python webhook bridges, multi-timeframe signal confluence aggregators, or automated order routing to MetaTrader 5 — tell us what you're building. We'll scope it, design it and deliver it to production standard.
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