TradeLab-MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@TradeLab-MCPCompile este EA e faça um backtest de PETR4 D1, entre 2015 e 2025, usando real ticks."
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.
TradeLab-MCP
MCP server for quantitative research. The AI defines the strategy. MetaTrader 5 Strategy Tester runs the backtest.
IA (Codex / GPT / Grok / Gemini / Claude)
│ MCP
▼
Trading Research MCP
│
▼
terminal64.exe → Strategy Tester oficial → runs/<run_id>/Fork of PHUICMT/mcp-mt5 (MIT). It does not reimplement the tester in Python.
Principle
MT5 is the authority for orders, fills, ticks, spread, SL/TP, margin, commissions, and P&L.
Python only organizes experiments (run_id, manifest, hashes, parser, derived statistics).
Each backtest generates a unique identifier. Nothing is retrieved by the “most recent file”.
runs/20260817_073412_a8f231/
tester.ini
strategy.mq5
strategy.ex5
report.htm
tester.log
trades.csv
metrics.json
manifest.jsonRelated MCP server: OpenFinClaw CLI
MCP Tools (V1)
Tool | Function |
| MT5, MetaEditor, terminal, data dir, Experts, Tester, build |
| Compiles |
| Official tester → |
| Same strategy, multiple assets, sequential |
| Retrieves an experiment by |
| Normalized trades from that |
| Metrics diff between runs |
| IS/OOS windows, each an official backtest |
| Compile + short tester (configurable symbol/period/model/date) |
Installation
Windows + MetaTrader 5 + Python 3.10+.
cd C:\Users\caioa\TradeLab-MCP
python -m pip install -e ".[dev]"MCP Client:
{
"mcpServers": {
"tradelab": {
"command": "tradelab-mcp",
"env": {
"MT5_INSTALL": "C:\\Program Files\\MetaTrader 5",
"TRADE_LAB_ROOT": "C:\\Users\\caioa\\TradeLab-MCP\\research"
}
}
}
}Variables: MT5_INSTALL, MT5_DATA, MT5_TERMINAL_HASH, TRADE_LAB_ROOT.
Example
Compile este EA e faça um backtest de PETR4 D1,
entre 2015 e 2025, usando real ticks.The agent calls run_backtest(strategy="experts/RSI2.mq5", symbol="PETR4", timeframe="D1", from_date="2015.01.01", to_date="2025.08.01", model=4) and receives:
{
"run_id": "20260817_073412_a8f231",
"status": "completed",
"symbol": "PETR4",
"period": "D1",
"model": "real_ticks",
"metrics": {
"total_trades": 134,
"net_profit": 18342.21,
"profit_factor": 1.48
}
}get_run("20260817_073412_a8f231") returns exactly that experiment.
Where EAs live in MT5
Every automated test EA is published to:
<MQL5>\Experts\TradeLab MCP\On this PC this resolves to:
C:\Users\caioa\AppData\Roaming\MetaQuotes\Terminal\D0E8209F77C8CF37AD8BF550E51FF075\MQL5\Experts\TradeLab MCP
In the Strategy Tester the expert appears as TradeLab MCP\RSI2. The folder is always relative to the active terminal (layout.experts_dir), not a fixed hash.
The source in git remains in experts/. The MCP copies source + .ex5 + local includes to the terminal folder.
The lab's base EA (CTrade, ArraySetAsSeries, one position) has not been standardized yet — it will come later, without rushing.
Acceptance EA
experts/RSI2.mq5
RSI(2)
buys if RSI < 10
exits if RSI > 70
one position
no optimization
Acceptance test #1 is: the same EA / asset / dates / inputs / capital / model in manual Strategy Tester and via MCP must produce the same metrics and the same trades.
Tests
pytestIntegration tests (Windows + real MT5):
$env:TRADE_LAB_INTEGRATION = "1"
$env:TRADE_LAB_SYMBOL = "EURUSD"
pytest tests/test_integration_mt5.py -vPriority
reproducibility > reliability > simplicity > speed > features
V1 is sequential (lock mt5.lock on the data directory). No parallel Python backtester. No .opt parser as official source.
This server cannot be installed
Maintenance
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