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

Related MCP server: metatrader5-mcp-server

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"
      ],
      "env": {
        "MT5_PATH": "C:\\Program Files\\MetaTrader 5\\terminal64.exe",
        "MT5_LOGIN": "<YOUR_ACCOUNT_NUMBER>",
        "MT5_PASSWORD": "<YOUR_PASSWORD>",
        "MT5_SERVER": "<YOUR_BROKER_SERVER>"
      }
    }
  }
}

The env block is optional. When it is set, initialize() and login() can be called without arguments and the agent never needs to see or ask for your credentials. Explicit arguments still take precedence. MT5_USERNAME is accepted as an alias for MT5_LOGIN.

Security: with credentials in the env block, the config file holds a secret. Keep it out of git, shared backups and shared or synced folders.

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

• MetaQuotes for the MetaTrader 5 platform

• FastMCP for the MCP server implementation