Which integrations are available for this server?

Uses .env files for configuration management, allowing secure storage of MetaTrader5 broker credentials through environment variables. Leverages pandas_ta library to provide technical indicators (SMA, EMA, RSI, MACD, Stochastic, Bollinger Bands) for market data analysis and charting. Provides access to MetaTrader5 terminal functionality including market data retrieval, historical rates, tick data, symbol information, and real-time market streaming through Python integration.

How do I use MetaTrader5 MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MetaTrader5 MCP Server get hourly EURUSD data for the last 24 hours" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

mtdata

mtdata is a research and automation toolkit for MetaTrader 5 (MT5). It provides tools for forecasting, regime detection, signal processing, risk analysis, and reporting—bridging raw market data with data science.

It runs as a Model Context Protocol (MCP) server or a standalone CLI.

Who Is This For?

Newer traders / learners: Follow guided workflows (no quant background required).
Systematic traders: Prototype ideas, backtest quickly, and automate via CLI/MCP.
Data folks: Pull MT5 market data into repeatable analysis pipelines.

Related MCP server: OKX MCP Server

Platform Support (Important)

Windows is required to run MetaTrader 5 (and therefore to run mtdata against MT5).
If you're on macOS/Linux, run mtdata on a Windows VM or Windows machine and connect remotely (MCP/Web API).

Safety First

mtdata includes trading_* commands that can place/modify/close real orders on the account currently logged into MT5.
Use a demo account until you understand the tools and your broker setup.
There is no built-in “paper trading” mode in mtdata; use an MT5 demo account for simulated execution.
If you only want research, stick to data_*, forecast_*, regime_*, patterns_*, and report_* commands.

Capabilities

Category	What It Does	Key Tools
Data	Fetch candles, ticks, market depth from MT5	`data_fetch_candles`, `data_fetch_ticks`, `market_depth_fetch`
Forecasting	Predict price paths with classical or ML models	`forecast_generate`, `forecast_backtest_run`
Volatility	Estimate future price movement magnitude	`forecast_volatility_estimate`
Regimes	Detect trending, ranging, or crisis market states	`regime_detect`
Barriers	Calculate TP/SL hit probabilities via simulation	`forecast_barrier_prob`, `forecast_barrier_optimize`
Patterns	Identify candlestick and chart patterns	`patterns_detect`
Indicators	Compute 100+ technical indicators	`data_fetch_candles --indicators`
Denoising	Smooth price data to reveal trends	`--denoise` option
Trading	Place orders, manage positions	`trading_place`, `trading_close`

Quick Start

Prerequisites: Windows + MetaTrader 5 installed and running (demo account recommended).

# Install dependencies pip install -r requirements.txt # Verify MT5 connection (lists symbols from the running terminal) python cli.py symbols_list --limit 5 # Fetch recent candles python cli.py data_fetch_candles EURUSD --timeframe H1 --limit 50 # Generate a baseline price forecast python cli.py forecast_generate EURUSD --timeframe H1 --horizon 12 --model theta

Documentation

New here? Follow this learning path: docs/SETUP.md → docs/GLOSSARY.md → docs/CLI.md → docs/SAMPLE-TRADE.md (then docs/SAMPLE-TRADE-ADVANCED.md and deep dives).

Getting Started

Setup & Configuration — Installation, MT5 connection, environment variables
CLI Guide — Command conventions, output formats, help system
Glossary — Explanations of all technical terms with real-world examples
Docs Index — One-page map of all docs

Core Topics

Forecasting — Price prediction methods (Theta, ARIMA, Chronos, etc.)
Volatility — Estimating price movement magnitude
Regime Detection — Identifying market states (trending vs. ranging)
Barrier Analysis — TP/SL hit probability calculation
Technical Indicators — Available indicators and usage
Denoising — Smoothing filters to reveal trends
Pattern Detection — Candlestick and chart patterns

Tutorials

Sample Trade Workflow — Step-by-step analysis for a trade decision
Advanced Playbook — Regime filters, conformal intervals, barrier optimization
End-to-End Example — Complete research loop with all tools

Reference

Troubleshooting — Common issues and fixes

Configuration

Create a .env file in the project root:

MT5_LOGIN=12345678 MT5_PASSWORD=your_password MT5_SERVER=your_broker_server MT5_TIME_OFFSET_MINUTES=0 # Adjust if broker server time differs from UTC

Architecture

mtdata/ ├── cli.py # CLI entry point ├── server.py # MCP server entry point ├── webui.py # Web API (FastAPI + React UI) ├── src/mtdata/ │ ├── core/ # Tool registry, schemas, server logic │ ├── forecast/ # Forecasting methods and engines │ ├── patterns/ # Pattern detection algorithms │ ├── services/ # MT5 data access layer │ └── utils/ # Shared utilities ├── webui/ # React + Vite frontend ├── docs/ # Documentation └── tests/ # Test suite