MetaTrader 5 API with Python: automate futures and Forex.

MQL5 (MetaTrader's native language) is powerful, but Python has an unbeatable ecosystem: pandas, numpy, scikit-learn, ready-made indicator libraries. The official MetaTrader5 library gives you the best of both worlds — you use Python to think and MT5 to execute. And the key point for you: it's the most accessible way to automate index futures and CFDs with Python.

01Installation and prerequisites

You need: Windows, your broker's MT5 terminal installed and logged in, and Python 3.11+. Then:

pip install MetaTrader5 pandas

02Connect to the terminal

With MT5 open and logged into your account (use a demo account!), initialize the connection:

# connect.py
import MetaTrader5 as mt5

# initialize the connection with the open MT5 terminal
if not mt5.initialize():
    print("Failed to connect:", mt5.last_error())
    quit()

# account info (confirm it's DEMO)
account = mt5.account_info()
print(f"Account: {account.login} | Balance: {account.balance} | Server: {account.server}")

# always close the connection when done
# mt5.shutdown()

If you need to log in via code (instead of manually in the terminal), pass credentials to initialize:

mt5.initialize(login=12345678, password="your_password", server="ServerName-Demo")

03Pull candles (including index futures)

Here's what connects to your indicators. Pull candles from any asset your broker offers — including index instruments like US500 or US30 if it gives access:

# data.py
import MetaTrader5 as mt5
import pandas as pd
from datetime import datetime

mt5.initialize()

# symbol: e.g. "US500" (S&P 500 index), "US30" (Dow) or "EURUSD"
# the exact symbol name varies by broker — check the Market Watch
symbol = "US500"
timeframe = mt5.TIMEFRAME_M5   # M1, M5, M15, H1, etc.

# get the last 500 candles
rates = mt5.copy_rates_from_pos(symbol, timeframe, 0, 500)
df = pd.DataFrame(rates)
df["time"] = pd.to_datetime(df["time"], unit="s")
print(df[["time","open","high","low","close","tick_volume"]].tail())

04Compute the signal with your indicators

This is where Python shines — use the indicator functions you've already learned in our guides. The DataFrame that came from MT5 plugs straight in:

# reuse the functions from the indicator guides
from indicators import compute_rsi, compute_macd   # your modules

df["rsi"] = compute_rsi(df["close"])
macd, signal, hist = compute_macd(df["close"])

# example of a combined signal
last = df.iloc[-1]
buy_signal = (last["rsi"] < 70) and (macd.iloc[-1] > signal.iloc[-1])

05Send an order

Sending an order in MT5 is more verbose than on Binance, because you build a detailed "request." Example of a market buy with a stop and target:

# executor.py
def buy(symbol, lot, stop_pts, target_pts):
    info = mt5.symbol_info_tick(symbol)
    price = info.ask
    point = mt5.symbol_info(symbol).point

    request = {
        "action": mt5.TRADE_ACTION_DEAL,
        "symbol": symbol,
        "volume": lot,
        "type": mt5.ORDER_TYPE_BUY,
        "price": price,
        "sl": price - stop_pts * point,   # stop loss
        "tp": price + target_pts * point, # take profit
        "deviation": 20,                   # tolerated slippage
        "magic": 123456,                  # your bot's id
        "type_filling": mt5.ORDER_FILLING_FOK,
    }
    result = mt5.order_send(request)
    if result.retcode != mt5.TRADE_RETCODE_DONE:
        print("Order error:", result.retcode, result.comment)
    return result

06Manage positions

For a complete bot, you need to query and close positions:

# query your bot's open positions (by magic)
positions = mt5.positions_get(symbol="US500")
for p in positions:
    if p.magic == 123456:
        print(f"Position {p.ticket}: profit {p.profit}")

# close a position
def close(position):
    tick = mt5.symbol_info_tick(position.symbol)
    request = {
        "action": mt5.TRADE_ACTION_DEAL,
        "symbol": position.symbol,
        "volume": position.volume,
        "type": mt5.ORDER_TYPE_SELL if position.type == 0 else mt5.ORDER_TYPE_BUY,
        "position": position.ticket,
        "price": tick.bid if position.type == 0 else tick.ask,
        "deviation": 20,
        "type_filling": mt5.ORDER_FILLING_FOK,
    }
    return mt5.order_send(request)

07The bot loop

Putting it all together, the skeleton of the MT5 bot:

import time

mt5.initialize()
try:
    while True:
        df = pull_candles("US500", mt5.TIMEFRAME_M5)
        signal = compute_signal(df)             # your strategy
        atr = compute_atr(df).iloc[-1]          # dynamic stop

        if signal == "BUY" and not has_position():
            lot = size_position(atr)            # risk management
            buy("US500", lot, stop_pts=2*atr, target_pts=4*atr)

        time.sleep(60)                       # check every minute
except Exception as e:
    print("Error:", e)
finally:
    mt5.shutdown()

08Frequently asked questions