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MCP Trader Server

by Af7007
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PyPI version

MetaTrader 5 MCP Server

A Model Context Protocol (MCP) server for MetaTrader 5, allowing AI assistants to interact with the MetaTrader 5 platform for trading and market data analysis. Documentation

Features

  • Connect to MetaTrader 5 terminal

  • Access market data (symbols, rates, ticks)

  • Place and manage trades

  • Analyze trading history

  • Integrate with AI assistants through the Model Context Protocol

Installation

From PyPI

uvx --from mcp-metatrader5-server mt5mcp

From Source

git clone https://github.com/Qoyyuum/mcp-metatrader5-server.git cd mcp-metatrader5-server uv sync uv run mt5mcp

Requirements

  • uv (recommended) or pip

  • Python 3.11 or higher

  • MetaTrader 5 terminal installed on Windows

  • MetaTrader 5 account (demo or real)

Usage

Quick Start

The server runs in stdio mode by default for MCP clients like Claude Desktop:

uv run mt5mcp

Development Mode (HTTP)

For testing with HTTP transport, create a .env file:

MT5_MCP_TRANSPORT=http MT5_MCP_HOST=127.0.0.1 MT5_MCP_PORT=8000

Then run:

uv run mt5mcp

The server will start at http://127.0.0.1:8000

Installing for MCP Clients

Method 1: Using uvx (Simplest - No Installation Required) ⭐

Add this configuration to your MCP client's config file:

For Claude Desktop (claude_desktop_config.json):

{ "mcpServers": { "mcp-metatrader5-server": { "command": "uvx", "args": [ "--from", "git+https://github.com/Qoyyuum/mcp-metatrader5-server", "mt5mcp" ] } } }

Method 2: Using FastMCP Install (Recommended)

git clone https://github.com/Qoyyuum/mcp-metatrader5-server cd mcp-metatrader5-server

After git cloning the repo, run the following commands:

For MCP JSON format

uv run fastmcp install mcp-json src/mcp_mt5/main.py

For Claude Desktop

uv run fastmcp install claude-desktop src/mcp_mt5/main.py

For Claude Code

uv run fastmcp install claude-code src/mcp_mt5/main.py

For Cursor

uv run fastmcp install cursor src/mcp_mt5/main.py

For Gemini CLI

uv run fastmcp install gemini-cli src/mcp_mt5/main.py

Method 3: Manual Configuration

Add this to your claude_desktop_config.json or whatever LLM config file:

{ "mcpServers": { "mcp-metatrader5-server": { "command": "uvx", "args": [ "--from", "mcp-metatrader5-server", "mt5mcp" ] } } }

API Reference

Connection Management

  • initialize(): Initialize the MT5 terminal

  • login(account, password, server): Log in to a trading account

  • shutdown(): Close the connection to the MT5 terminal

Market Data Functions

  • get_symbols(): Get all available symbols

  • get_symbols_by_group(group): Get symbols by group

  • get_symbol_info(symbol): Get information about a specific symbol

  • get_symbol_info_tick(symbol): Get the latest tick for a symbol

  • copy_rates_from_pos(symbol, timeframe, start_pos, count): Get bars from a specific position

  • copy_rates_from_date(symbol, timeframe, date_from, count): Get bars from a specific date

  • copy_rates_range(symbol, timeframe, date_from, date_to): Get bars within a date range

  • copy_ticks_from_pos(symbol, start_pos, count): Get ticks from a specific position

  • copy_ticks_from_date(symbol, date_from, count): Get ticks from a specific date

  • copy_ticks_range(symbol, date_from, date_to): Get ticks within a date range

Trading Functions

  • order_send(request): Send an order to the trade server

  • order_check(request): Check if an order can be placed with the specified parameters

  • positions_get(symbol, group): Get open positions

  • positions_get_by_ticket(ticket): Get an open position by its ticket

  • orders_get(symbol, group): Get active orders

  • orders_get_by_ticket(ticket): Get an active order by its ticket

  • history_orders_get(symbol, group, ticket, position, from_date, to_date): Get orders from history

  • history_deals_get(symbol, group, ticket, position, from_date, to_date): Get deals from history

Example Workflows

Connecting and Getting Market Data

# Initialize MT5 initialize() # Log in to your trading account login(account=123456, password="your_password", server="your_server") # Get available symbols symbols = get_symbols() # Get recent price data for EURUSD rates = copy_rates_from_pos(symbol="EURUSD", timeframe=15, start_pos=0, count=100) # Shut down the connection shutdown()

Placing a Trade

# Initialize and log in initialize() login(account=123456, password="your_password", server="your_server") # Create an order request request = OrderRequest( action=mt5.TRADE_ACTION_DEAL, symbol="EURUSD", volume=0.1, type=mt5.ORDER_TYPE_BUY, price=mt5.symbol_info_tick("EURUSD").ask, deviation=20, magic=123456, comment="Buy order", type_time=mt5.ORDER_TIME_GTC, type_filling=mt5.ORDER_FILLING_IOC ) # Send the order result = order_send(request) # Shut down the connection shutdown()

Resources

The server provides the following resources to help AI assistants understand how to use the MetaTrader 5 API:

  • mt5://getting_started: Basic workflow for using the MetaTrader 5 API

  • mt5://trading_guide: Guide for placing and managing trades

  • mt5://market_data_guide: Guide for accessing and analyzing market data

  • mt5://order_types: Information about order types

  • mt5://order_filling_types: Information about order filling types

  • mt5://order_time_types: Information about order time types

  • mt5://trade_actions: Information about trade request actions

Prompts

The server provides the following prompts to help AI assistants interact with users:

  • connect_to_mt5(account, password, server): Connect to MetaTrader 5 and log in

  • analyze_market_data(symbol, timeframe): Analyze market data for a specific symbol

  • place_trade(symbol, order_type, volume): Place a trade for a specific symbol

  • manage_positions(): Manage open positions

  • analyze_trading_history(days): Analyze trading history

Development

Project Structure

mcp-metatrader5-server/ ├── src/ │ └── mcp_mt5/ │ ├── __init__.py # Entry point with main() │ ├── main.py # FastMCP server with all tools │ └── test_client.py # Test client for development ├── docs/ │ ├── getting_started.md │ ├── market_data_guide.md │ ├── trading_guide.md │ └── publishing.md ├── .env # Environment configuration (create from .env.example) ├── README.md ├── pyproject.toml # Project metadata (using hatchling) └── uv.lock # Dependency lock file

Building the Package

Using uv (recommended):

uv build

This will create wheel and source distributions in the dist/ directory.

Publishing to PyPI

Using uv:

# Build first uv build # Publish to PyPI uv publish # Or publish to TestPyPI first uv publish --publish-url https://test.pypi.org/legacy/

License

MIT

Acknowledgements

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