Full architecture breakdown:
https://t.co/hXNcdtZv8w
Not a tutorial β a design spec. Feed it to your OpenClaw, Claude, or GPT and ask it to scaffold the relay.
You fill in the logic. Plumbing is the easy part.
In MT4, after a trade executes, it falls into a void.
No feedback. No structure. Your EA fires an order, gets a return code, and that's it. Slippage? Actual ticket? Who knows.
I built a FastAPI hack to parse journal logs just to find out.
MT5 killed that pain. π§΅
The stack runs local. No cloud API knows your positions.
OpenClaw emits semantic commands β relay β MQL5 EA executes β structured feedback loops back.
Three layers. The thinnest possible bridge.
Current Status: 85% complete! ποΈ
The Python side is stable; final MQL4 error handling is in progress.
Read the full architecture breakdown on my blog: https://t.co/9xSKq7I0cY
#AlgorithmicTrading#MT4#FinTech#AI#OpenClaw
Bridging the gap between modern AI and legacy trading systems isnβt easy. π
I just published a deep dive into how I architected a low-latency bridge between the OpenClaw AI framework and MetaTrader 4 (MT4).
A thread on risk automation and local AI π§΅π
The "Secret Sauce": Prompting is the Architecture. π€
The FastAPI & MQL4 boilerplate was largely scaffolded by prompting OpenClaw itself. The goal isn't just writing code, but compressing the gap between "concept" and "execution." #OpenClaw#LLM#SystemArchitecture