How to Connect MetaTrader 5 to TradingView: Practical Guide to Real-Time Trade Execution

Author: Jameson Richman Expert

Published On: 2025-11-12

Prepared by Jameson Richman and our team of experts with over a decade of experience in cryptocurrency and digital asset analysis. Learn more about us.

If you want to learn how to connect MetaTrader 5 to TradingView, this comprehensive guide will walk you through practical, secure, and tested methods to forward alerts from TradingView into live orders on MT5. You’ll get step-by-step instructions, example code (Python + MT5), alert message templates, troubleshooting tips, symbol-mapping advice, and recommended best practices for reliability and safety.


Table of contents

Table of contents

Why connect TradingView to MetaTrader 5?

TradingView is exceptional for charting and scripting strategies with Pine Script. MetaTrader 5 is widely used for executing orders on forex and CFD brokers, and supports advanced order types and expert advisors. Connecting TradingView to MT5 lets you:

  • Use TradingView indicators and strategies to generate trade signals.
  • Automatically execute those signals in an MT5 account (live or demo).
  • Combine powerful charting and social features (TradingView) with broker execution and order management (MT5).

Overview of proven methods

There are three common approaches to bridge TradingView signals to MetaTrader 5:

  1. Webhook to your own server (recommended): TradingView alerts call a webhook URL; your server receives the JSON and a Python script (using the MetaTrader5 module) places orders on MT5.
  2. Commercial bridge services: Use services like PineConnector or other third-party connectors that handle webhook routing and placing trades on MT5/EAs on your machine or VPS.
  3. EA-based polling or mail/webrequest: Create an MQL5 Expert Advisor that polls an endpoint or reads messages (less common and more complex).

Prerequisites — what you need before you start

Prerequisites — what you need before you start

  • An installed MetaTrader 5 terminal (or a VPS running MT5) with an account logged in and allowed automated trading.
  • A TradingView account (Pro or higher for webhook support; free accounts may be limited).
  • A public webhook endpoint (hosted on a VPS, cloud function, or tunneling service like ngrok for testing).
  • Python 3.x, pip, and the official MetaTrader5 Python package (or an EA/connector if you choose that route).
  • Basic coding comfort (editing a Flask app, starting/stopping a service).

Note: If you prefer not to run your own code, commercial bridge providers simplify setup at the cost of subscription fees.

Method 1 — TradingView webhook → Flask/Python → MT5 (recommended)

This method gives you full control, low latency (when hosted on a VPS), and transparency. It requires running a small Python service that receives TradingView webhook alerts and forwards instructions to MT5 using the MetaTrader5 Python package.

Step 1 — Install MetaTrader5 Python package

On the machine where MetaTrader 5 is installed (same machine or a VPS with MT5), install the package:

pip install MetaTrader5 flask

Step 2 — Minimal Flask webhook server

Below is a minimal, tested Flask app that receives TradingView alerts (JSON), parses them, and places a market order in MT5. Save as webhook_mt5.py.

from flask import Flask, request, jsonify
import MetaTrader5 as mt5
import json
import time

app = Flask(__name__)

# Initialize MT5 (MT5 terminal must be running on this machine or credentials provided)
if not mt5.initialize():
    print("initialize() failed, error code =", mt5.last_error())
    # You may include mt5.shutdown() and retry logic here

ACCOUNT = 12345678    # replace with your MT5 account number (or remove for auto)
PASSWORD = "password" # replace with account password if needed
SERVER = "Broker-Server" # replace with broker server name if needed

# Optionally login
# mt5.login(ACCOUNT, PASSWORD, SERVER)


def send_market_order(symbol, action, volume=0.01, sl=0, tp=0, deviation=10):
    # action: "buy" or "sell"
    symbol_info = mt5.symbol_info(symbol)
    if symbol_info is None:
        return {"error": f"Symbol {symbol} not found in MT5"}
    if not symbol_info.visible:
        mt5.symbol_select(symbol, True)
    point = symbol_info.point
    price = mt5.symbol_info_tick(symbol).ask if action.lower()=="buy" else mt5.symbol_info_tick(symbol).bid

    request = {
        "action": mt5.TRADE_ACTION_DEAL,
        "symbol": symbol,
        "volume": float(volume),
        "type": mt5.ORDER_TYPE_BUY if action.lower()=="buy" else mt5.ORDER_TYPE_SELL,
        "price": price,
        "sl": float(sl) if sl else 0.0,
        "tp": float(tp) if tp else 0.0,
        "deviation": int(deviation),
        "magic": 123456,
        "comment": "TV->MT5",
        "type_filling": mt5.ORDER_FILLING_FOK,
    }

    result = mt5.order_send(request)
    return result._asdict() if result else {"error": "order_send returned None"}


@app.route('/webhook', methods=['POST'])
def webhook():
    try:
        data = request.get_json(force=True)
    except Exception as e:
        return jsonify({"error": "Invalid JSON", "exception": str(e)}), 400

    # Example expected payload: {"symbol":"EURUSD","action":"buy","volume":0.1,"sl":1.0980,"tp":1.1120}
    symbol = data.get("symbol")
    action = data.get("action")
    volume = data.get("volume", 0.01)
    sl = data.get("sl", 0)
    tp = data.get("tp", 0)
    if not symbol or not action:
        return jsonify({"error": "Missing symbol or action"}), 400

    result = send_market_order(symbol, action, volume, sl, tp)
    return jsonify({"status": "received", "data": data, "result": result})


if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

Important notes:

  • Run this script on the same machine where MT5 is installed, or ensure mt5.initialize() correctly connects to the broker.
  • Adjust account/login logic if multiple accounts or credentials are required. The MetaTrader5 Python package requires the MT5 terminal to be running for many setups.
  • Use a VPS for production to ensure continuous operation and low latency.

Step 3 — Create a TradingView alert that posts to your webhook

On TradingView, create an alert and enable the "Webhook URL" field. Use your publicly accessible endpoint, for example:

Webhook URL: https://your-vps-domain.com/webhook

Set the alert message to JSON. An example message:

{
  "symbol": "EURUSD",
  "action": "buy",
  "volume": 0.1,
  "sl": 1.0810,
  "tp": 1.0920
}

When the alert triggers, TradingView will POST this JSON to your Flask server, which will route it into MT5.

Step 4 — Run and monitor

  • Start the Flask app (consider using systemd or a supervisor in production).
  • Check MT5 > Tools > Journal and Experts for order logs when requests are processed.
  • Keep robust logging in your Flask app (file-based logs or a logging service).

Method 2 — Use a commercial connector (PineConnector and others)

If you prefer a plug-and-play solution, connectors like PineConnector, Botsfolio, or other paid services provide a ready-made bridge:

  • They supply an Expert Advisor (EA) to run on your MT5 terminal and a webhook endpoint to paste into TradingView.
  • Advantages: minimal coding, support, polished UI, and built-in security practices.
  • Disadvantages: monthly fees, third-party trust, and sometimes limited customization.

Before choosing a provider, verify reviews, security, and whether they specifically support MT5 (not just MT4). Always run on a demo account first.


How to create TradingView alerts and webhook payloads (detailed)

How to create TradingView alerts and webhook payloads (detailed)

You must format alerts so your server expects them. Common approaches:

  1. Simple JSON with fields: symbol, action (buy/sell), volume, sl, tp.
  2. Include a “key” or token in the JSON or URL for authentication: e.g., {"token":"mysecret","symbol":"BTCUSD"...}.
  3. Use an alert script in Pine Script to build dynamic messages with strategy.entry calls or custom messages.

Example TradingView message using Pine Script variables:

//@version=4
strategy("Alert example", overlay=true)
longCondition = crossover(sma(close,14), sma(close,28))
if (longCondition)
    strategy.entry("Long", strategy.long)
alert_message = '{"symbol":"'+syminfo.ticker+'","action":"buy","volume":0.01}'
alert(alert_message, alert.freq_once_per_bar)

Important: TradingView uses symbol names specific to its data provider. You may need to map TradingView symbols to broker symbols used in MT5.

Symbol mapping and common pitfalls

Symbol mismatches are a frequent cause of errors:

  • TradingView may use "EURUSD" while your broker uses "EURUSDm" or "EURUSDpro".
  • Crypto symbols may differ massively (BTCUSDT vs BTCUSD). Check the exact symbol in MT5's Market Watch.
  • Prepend or transform symbols in your webhook receiver (add suffixes or prefixes) to match MT5.

Implement a mapping dictionary in your webhook service, e.g.:

symbol_map = {"BTCUSD": "BTCUSDm", "EURUSD": "EURUSD"} 
mt5_symbol = symbol_map.get(tv_symbol, tv_symbol)

Security, reliability and deployment tips

Running automated trading systems requires strong operational controls:

  • Use an authentication token in the webhook (e.g., include "token" in JSON and validate it).
  • Host the webhook on a secure VPS (AWS, DigitalOcean, Hetzner) with HTTPS and firewall rules.
  • Run MT5 and your bridge process on the same machine or within the same private network for security.
  • Limit access to the webhook URL (IP allow list where possible).
  • Keep MT5’s automated trading switch and relevant Expert Advisors configured safely.
  • Implement rate limiting and request validation to avoid malformed orders.

Testing, logging and dry-run recommendations

Testing, logging and dry-run recommendations

Before going live:

  1. Test on a demo account. Never test live until the system behaves consistently on demo for a prolonged period.
  2. Enable verbose logging in your Flask app and MT5. Save request payloads and order responses.
  3. Use simulated “dry-run” mode: have your server validate payloads and only log actions rather than send orders. Add a "test": true flag to alert JSON.
  4. Set conservative default volumes and stop-loss parameters during early tests.

FAQ and troubleshooting

Q: My webhook receives the alert but MT5 returns symbol not found. What do I do?

Check exact symbol names in MT5 Market Watch. Implement mapping in your server to convert TradingView symbols to MT5 symbols.

Q: TradingView says “Webhook URL unreachable”.

Ensure your endpoint is publicly reachable over HTTPS and that your server certificates are valid. For testing, use ngrok to tunnel from your local machine (remember ngrok URLs change unless using a paid plan).

Q: Orders are rejected due to “volume too small” or “invalid stops”.

Check your broker’s minimum lot size and stop-distance rules. Adjust the volume/SL/TP in your payload accordingly.

Q: How long is latency between TradingView alert and MT5 order?

Latency depends on your webhook host. A VPS in the same region as TradingView servers and your broker will typically yield the lowest latency. Expect sub-second to a few seconds if well-configured.

Further reading and useful links

For advanced traders and developers: if you want to build automated crypto trading bots or arbitrage systems that connect exchanges and platforms, these practical guides may help:

If you trade crypto and need exchange accounts for hedging or dual-execution strategies, these registration links can help you get started (affiliate links):


Best practices summary

Best practices summary

  • Always start with a demo account and perform staged testing (unit tests, dry-run, demo, limited live).
  • Use secure webhooks and authentication tokens; host on a trusted VPS with HTTPS.
  • Implement symbol mapping to avoid order rejections from mismatched tickers.
  • Monitor logs and set up alerts for failed order attempts or connectivity issues.
  • Consider using a commercial connector if you want a faster, maintenance-free setup, but vet their security and fees.

Closing notes

Connecting TradingView to MetaTrader 5 opens powerful possibilities: visually-rich signal generation combined with robust broker execution. Whether you choose to build a custom webhook-to-MT5 bridge using Python and the MetaTrader5 package or you select a commercial connector, the most important factors are testing, security, and clear symbol/volume rules.

Use the example Flask app above as a starting point and extend it with authentication, order validation, mapping, and robust logging. For more advanced trading bot development patterns and step-by-step bot guides you can adapt to MT5 workflows, see the linked bot-building resources earlier in this article.

If you want, I can provide a ready-to-run GitHub-style repository layout for the Flask bridge (including config, logging, and Dockerfile) or show a sample MQL5 EA that complements the Python solution. Which would you prefer?

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