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MetaTrader 5

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MCP server for MetaTrader 5 trading platform, enabling AI assistants to access market data and execute trades.

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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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