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MetaTrader 5 MCP Server

MetaTrader 5 MCP Server

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pypi.orgFinance238Updated 1d ago

About MetaTrader 5 MCP Server

MetaTrader 5 MCP Server is an MCP server for the MetaTrader 5 trading platform. It lets AI assistants access market data, place trades and review trading history. It suits users who want AI help with MT5 market analysis or trading workflows.

Key features

  1. 01Connects to MetaTrader 5 terminal and trading accounts
  2. 02Retrieves symbols, bars and tick data
  3. 03Places orders and queries positions and pending orders
  4. 04Queries order and deal history

Use cases

  1. 01Letting an AI assistant look up symbol quotes and historical bars
  2. 02Checking and submitting trade orders from a chat interface
  3. 03Reviewing trading history over a chosen period

MCP support

This project is an MCP server that exposes MetaTrader 5 connection, market data, trading and history functions as tools and resources to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"metatrader5-server": {
"command": "uvx",
"args": [
"mcp-metatrader5-server"
]
}
}
}
Run commanduvx mcp-metatrader5-server

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypimcp-metatrader5-server

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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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

Comments

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