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Boschi404

MT5 MCP Server

by Boschi404
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Python
Local

MT5 MCP Server v2.1

37-tool MCP server for MetaTrader 5 — the most complete LLM-to-MT5 bridge. Full autonomous pipeline from strategy description to PDF report, with proper risk metrics (Sharpe, Sortino, Calmar) and validation checks. Write EAs, compile, backtest, optimize, Monte Carlo, Kelly sizing, live trade, monitor portfolio — all through MCP.

FastMCP Python MT5 Tools Release

Highlights

  • 🤖 Autonomous Pipeline — Describe a strategy → get a complete PDF report with Monte Carlo, Kelly, risk metrics

  • 📊 37 MCP tools — every MT5 operation available to LLMs

  • 📈 Proper Risk Metrics — Annualized Sharpe, Sortino, Calmar with sanity checks

  • 🔴 Live Trading — Place orders, manage positions, monitor portfolio from any LLM

Related MCP server: OpenFinClaw CLI

Tools Overview (37)

📊 Backtest & Optimization (5)

Tool

Description

run_mt5_backtest

Single backtest with full parameter control

run_mt5_optimization

Genetic/complete parameter optimization

run_multi_backtest

Test EA on multiple symbols, aggregate results

get_backtest_results

Parse tester log into structured trade data

get_optimization_results

Read .opt files with best passes

✏️ EA Development (6)

Tool

Description

write_expert

Write/update .mq5 source (auto-compile)

compile_expert_file

Compile .mq5 → .ex5 via MetaEditor

read_expert_code

Read full MQL5 source

get_ea_parameters

Extract all input params with types/defaults

list_experts

List all installed EAs

get_backtest_log

Raw tester log for debugging

📈 Advanced Analytics (6)

Tool

Description

run_monte_carlo

1000-sim robustness with P5/P95 confidence

run_walk_forward

Rolling OOS validation, overfitting detection

calc_position_size

Kelly Criterion, Optimal F, Risk of Ruin

get_trade_stats

Expectancy, Z-score, streaks

get_risk_metrics

v2.1 Sharpe, Sortino, Calmar + validation

export_trades

Export results to CSV

🔴 Live Trading (6)

Tool

Description

place_order

Market & pending orders (buy/sell/limit/stop)

get_positions

Open positions with real-time P&L

close_position

Close by ticket or close all

modify_position

Modify SL/TP on open positions

get_account

Balance, equity, margin, leverage

get_order_history

Historical deals with P&L

📊 Portfolio Management (7)

Tool

Description

analyze_portfolio_diversification

0-100 score + verdict + recommendations

calc_correlation

Correlation matrix, diversification score

calc_efficient_frontier

Markowitz optimal weights, max Sharpe

calc_risk_allocation

Equal risk, Kelly, inverse-DD allocation

get_portfolio_health

Live P&L, concentration, margin

backtest_to_returns

Convert results to returns series

get_mt5_status

Connection and account status

🤖 Autonomous Pipeline (2)

Tool

Description

build_strategy_code

v2.0 Generate MQL5 EA from natural language

run_autonomous_pipeline

v2.0 Full auto: Create→Compile→Screen→Correlate→Optimize→MC→Kelly→Robustness→Report

📡 Data Access (5)

Tool

Description

get_bars

OHLC bar data for any symbol/timeframe

get_ticks

Raw tick data with spread stats

list_symbols

All available trading symbols

get_latest_price

Real-time bid/ask for multiple symbols

get_symbol_info

Spread, swap, margin, tick value

Quick Start

git clone https://github.com/Boschi404/mt5-mcp-server.git
cd mt5-mcp-server
pip install -r requirements.txt

Register with MCP Client

Hermes Agent:

hermes mcp add mt5-backtest --command "C:/Python311/python" --args "/path/to/server.py" --timeout 600

Claude Desktop (claude_desktop_config.json):

{"mcpServers": {"mt5-backtest": {"command": "python", "args": ["/path/to/server.py"]}}}

Autonomous Pipeline

One command to run 9 phases:

run_autonomous_pipeline(
    strategy_name="GoldBreakout",
    strategy_description="Channel breakout M15, EMA50 H4 trend filter, SL 700pts, TP 3000pts"
)

Phases:

  1. Create — Generate MQL5 code with all parameters

  2. Compile — Compile to .ex5 + error check

  3. Screen — Test on 15+ major symbols (1M OHLC)

  4. Correlate — Find uncorrelated candidates (0-100 diversification score)

  5. Optimize — Genetic optimization on tick data with fixed risk

  6. Monte Carlo — 1000 simulations, skip 10% random trades

  7. Kelly — Position sizing from real trade stats (max 15% DD)

  8. Robustness — 100 random 6-month backtests

  9. Report — Full HTML report with Sharpe, Sortino, Calmar + validation

Output: Desktop/pipelines/StrategyName_TIMESTAMP/ with organized subfolders per phase.

Risk Metrics (v2.1)

get_risk_metrics computes proper risk-adjusted returns:

Metric

Formula

Sharpe

(Return − RiskFree) / StdDev × √Periods

Sortino

(Return − RiskFree) / DownsideStdDev × √Periods

Calmar

AnnualizedReturn / MaxDrawdown

Automatic validation checks:

  • Sharpe > 10? → ⚠️ WARNING: suspiciously high

  • Sortino >> Sharpe? → ✅ Positive skew confirmed

  • Profit Factor > 100? → ⚠️ WARNING: likely look-ahead bias

  • Win Rate > 95%? → ⚠️ WARNING: survivorship bias

Example Workflows

Full Pipeline (EA → Live)

1. build_strategy_code("Channel breakout, SL 700, TP 3000") → get MQL5 code
2. write_expert("GoldScalper", code)                         → save + compile
3. run_multi_backtest("GoldScalper", ["XAUUSD","DAXEUR","NDQUSDc"]) → screen
4. analyze_portfolio_diversification(returns)                → score: 72/100 ✅
5. run_autonomous_pipeline("GoldScalper")                    → full auto
6. place_order("XAUUSD", "buy_stop", volume=0.05, ...)      → go live
7. get_portfolio_health()                                    → monitor

Risk Check

LLM → get_risk_metrics()
→ Sharpe: 1.85 (institutional quality)
→ Sortino: 3.12 (positive skew)
→ Max DD: 8.4%
→ Data Quality: GOOD
→ Validation: 3 checks passed, 0 warnings

Architecture

mt5-mcp-server/
├── server.py              # MCP server (37 tools)
├── backtest.py            # MT5 tester orchestrator
├── analytics.py           # Monte Carlo, Walk-Forward, Kelly
├── risk_metrics.py        # v2.1 Proper Sharpe/Sortino/Calmar
├── trading.py             # Live order execution
├── portfolio.py           # Correlation, efficient frontier
├── data.py                # Bar/tick data, symbols, prices
├── batch.py               # Multi-symbol testing
├── pipeline.py            # v2.0 Autonomous pipeline orchestrator
├── strategy_builder.py    # v2.0 MQL5 code generator
├── report_generator.py    # v2.0 HTML/PDF report generator
└── requirements.txt

Version History

Version

Tools

Highlights

v1.0

5

Basic backtest + log parsing

v1.1

11

Optimization, EA dev, compilation

v1.2

17

Monte Carlo, Walk-Forward, Kelly, CSV

v1.3

30

Live trading, portfolio, data access

v1.4

34

Batch testing, diversification scoring

v2.0

36

Autonomous pipeline, strategy builder, PDF reports

v2.1

37

Proper Sharpe/Sortino/Calmar + validation checks

License

MIT — use it, fork it, ship it.

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