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emerzon

MetaTrader5 MCP Server

by emerzon
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Python
Local

mtdata

Turn MetaTrader 5 into a research lab you can script, query from AI agents, or browse in a local web UI.

mtdata is a Windows-first toolkit that sits on top of a running MT5 terminal. It gives you 90+ tools for market data, forecasting, regime detection, patterns, risk, and trading through the CLI and MCP, plus a focused FastAPI Web API for selected workflows.

It is a toolkit for exploration and automation, not a trading strategy or financial advice.

Why mtdata?

Strength

What that means for you

One stack, three surfaces

Full tool surface through mtdata-cli and MCP; focused HTTP workflows through a local Web API + React UI

Research depth

Classical, ML, and foundation forecasting; regimes; barriers; patterns; 100+ indicators; denoising

MT5-native

Candles, ticks, market scans, account/positions, and real order flow against your broker terminal

Agent-friendly

Designed for tool-calling workflows: structured outputs, async training, dry-run trading

Safety-aware

Demo-first guidance, optional trade guardrails, and dry-run previews on trading commands

Guided learning

Sample trade workflows, a glossary, and docs that go from “first candle fetch” to advanced playbooks

If you already live in MT5 and want repeatable analysis — or you want an assistant to pull data and run forecasts without reinventing the glue — this repo is built for that.

Related MCP server: MetaTrader 5 MCP Server

Who is this for?

  • Learners & discretionary traders — Follow guided workflows without a quant background. Start with candles, a simple forecast, and the sample trade guide.

  • Systematic / quant-curious traders — Prototype ideas, backtest, optimize barriers, and automate via CLI or MCP.

  • Builders & data folks — Pull MT5 data into pipelines, agents, or a local web stack with a consistent output contract.

Platform notes

Requirement

Detail

Windows

Required to run MetaTrader 5 (and therefore mtdata against MT5)

macOS / Linux

Run mtdata on a Windows machine or VM; connect remotely via MCP or Web API

Python

3.14 is the supported runtime for the packaged dependency set

Safety first

trade_* tools can place, modify, and close real orders on the account logged into MT5.

  • Prefer a demo account until you know the tools and your broker behavior.

  • There is no separate paper-trading mode inside mtdata — use an MT5 demo account for simulated execution.

  • When a command supports --dry-run true, use it to preview before anything hits the broker.

  • For research only, stick to data_*, forecast_*, regime_*, patterns_*, and report_*.

Optional guardrails (allowed symbols, max volume, max risk % of equity) are documented in docs/ENV_VARS.md and docs/TRADING_SAFETY.md.

What you can do

Area

Highlights

Example tools

Data

Candles, ticks, depth (optional), market scans

data_fetch_candles, data_fetch_ticks, symbols_top_markets

Forecasting

Theta → ARIMA/ML → Chronos-class foundation models; async train & model cache

forecast_generate, forecast_backtest_run, forecast_train

Volatility & barriers

Movement estimates; TP/SL hit probabilities via simulation

forecast_volatility_estimate, forecast_barrier_prob

Regimes

Trending / ranging / stress-style market states

regime_detect

Patterns & levels

Candlesticks, chart patterns, Elliott/fractals; pivots & confluence

patterns_detect, level tools

Indicators & denoise

100+ technicals; smooth noise to see structure

--indicators, --denoise

Multi-asset & diagnostics

Correlation, cointegration, stationarity, outliers, seasonality

correlation_matrix, stationarity_test, outliers_detect

Strategy & risk

Simple rule backtests; VaR/CVaR, stress, position sizing

strategy_backtest, trade_var_cvar_calculate

Trading

Place/manage orders with guardrails when you opt in

trade_place, trade_close

News & fundamentals

Ranked news/calendar; Finviz equity screens

news, finviz_screen

Options

Chains + QuantLib barrier pricing

options_chain, options_barrier_price

Reports

Packaged research-style summaries

report_generate

Notes

  • market_depth_fetch requires MTDATA_ENABLE_MARKET_DEPTH_FETCH=1 and broker Level 2/DOM data.

  • Options chains default to Yahoo Finance; Tradier is available with env config. Pure QuantLib pricing does not need a chain provider.

For method-level detail, see docs/FORECAST.md and docs/forecast/METHODS.md.

Three ways to use it

                    ┌─────────────────┐
                    │  MetaTrader 5   │
                    │   (Windows)     │
                    └────────┬────────┘
                             │
                      ┌──────▼──────┐
                      │   mtdata    │
                      └──────┬──────┘
           ┌─────────────────┼─────────────────┐
           ▼                 ▼                 ▼
      mtdata-cli          MCP server        Web API
   (scripts, REPL)    (AI assistants)    (+ React UI)

Surface

Entry point

Good for

CLI

mtdata-cli

Scripts, exploration, copy-paste workflows

MCP

mtdata-stdio / mtdata-sse / mtdata-streamable-http

Agent tool use (Claude, Cursor, custom clients)

Web

mtdata-webapi

Local UI and HTTP integrations

Quick start

Prerequisites: Windows + Python 3.14 + MetaTrader 5 installed and running (demo recommended). For the full research stack, install Visual Studio Build Tools 2022 with Desktop development with C++.

# Optional: isolate the environment
conda create -n mtdata python=3.14 -y
conda activate mtdata

# Lean core (data, indicators, core analysis)
pip install -e .

# Or full validated research + web stack
pip install -r requirements.txt

# Confirm MT5 sees your terminal
mtdata-cli symbols_list --limit 5

# Rank markets from the current watchlist
mtdata-cli symbols_top_markets --rank-by all --limit 5 --timeframe H1

# Pull candles
mtdata-cli data_fetch_candles EURUSD --timeframe H1 --limit 50

# Baseline forecast
mtdata-cli forecast_generate EURUSD --timeframe H1 --horizon 12 --method theta

Keep the first session read-only unless you are on a demo account and intentionally testing trading.

Install flavors (summary)

Goal

Command

Lean core

pip install -e .

Full docs-aligned stack

pip install -r requirements.txt

Web only

pip install -e .[web]

Classical / foundation forecast extras

pip install -e .[forecast-classical] / pip install -e .[forecast-foundation]

Git-backed add-ons (TimesFM, etc.)

See docs/SETUP.md

Dependency caveats (NeuralForecast optional installs, Python 3.14 exclusions, optional native accelerators) live in Setup so this page stays focused on getting you productive.

Documentation

Suggested path: Setup → Glossary → CLI → Sample trade → deeper topics as needed.

Start here

Then explore

Setup & configuration

Troubleshooting, Env vars

CLI guide · Glossary (BOCPD, Kelly, …)

Output contract, Timestamps

Sample trade

Advanced playbook, End-to-end example

Forecasting

Methods, Backtesting, Uncertainty

Regimes · Barriers · Patterns

Indicators, Levels, Denoising

Trading safety · Risk analytics

Web API, Deployment

Docs index

Full map of every guide

Configuration

Create a .env in the project root (never commit credentials):

MT5_LOGIN=12345678
MT5_PASSWORD=your_password
MT5_SERVER=your_broker_server
MT5_SERVER_TZ=Europe/Athens   # optional broker session/calendar timezone

# Optional trade guardrails
MTDATA_TRADE_GUARDRAILS_ENABLED=1
MTDATA_TRADE_ALLOWED_SYMBOLS=EURUSD,BTCUSD,XAUUSD
MTDATA_TRADE_MAX_VOLUME_BY_SYMBOL=EURUSD:0.50,BTCUSD:0.03
MTDATA_TRADE_MAX_RISK_PCT_OF_EQUITY=1.5

Full reference: docs/ENV_VARS.md.

Project layout

mtdata/
├── src/mtdata/
│   ├── bootstrap/   # Runtime init, settings, tool loading
│   ├── core/        # CLI, MCP/server, trading, regime, report tools
│   ├── forecast/    # Engines, methods, model store, async tasks
│   ├── patterns/    # Chart / candlestick / structure detection
│   ├── services/    # MT5 gateway, Finviz, options, news
│   ├── shared/      # Schemas and shared constants
│   └── utils/       # Indicators, denoising, helpers
├── webui/           # React + Vite frontend
├── docs/            # User guides and references
└── tests/           # Pytest suite

License

MIT

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