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@Qoyyuum/mcp-metatrader5-server

MCP server for MetaTrader 5 market data and trades

This repo provides an MCP server that sits between an agent and the MetaTrader 5 terminal. Through the server, the agent can connect to MT5, read symbols and price data, place and check orders, and inspect positions and trading history.

218 stars77 forksPythonUpdated 10d ago
Who it's for

Builders who want their agent to read MetaTrader 5 data and manage trades.

What it delivers

You can let an agent query market data, place orders, and analyze trading history without leaving your MCP client.

What it does

Terminal connection and login

Tools to initialize the MT5 terminal, log in to an account, and shut the connection down.

Market data access

Tools for symbols, symbol info, ticks, rates, and tick or bar ranges by position or date.

Trading actions

Tools for sending and checking orders, plus reading open positions and active orders.

Trading history access

Tools to pull historical orders and deals by symbol, ticket, position, or date range.

Agent guidance resources

Built-in `mt5://` resources and prompts for getting started, market data, trading, and history analysis.

MCP client setup examples

Installation examples for Claude Desktop, Claude Code, Cursor, and Gemini CLI using FastMCP or `uvx`.

How to get it

  1. 1Run
    uvx --from mcp-metatrader5-server mt5mcp
  2. 2Run
    git clone https://github.com/Qoyyuum/mcp-metatrader5-server.git
    cd mcp-metatrader5-server
    uv sync
    uv run mt5mcp
  3. 3The server runs in stdio mode by default for MCP clients like Claude Desktop
    uv run mt5mcp
  4. 4Then run
    uv run mt5mcp
  5. 5Run
    git clone https://github.com/Qoyyuum/mcp-metatrader5-server
    cd mcp-metatrader5-server
  6. 6For MCP JSON format
    uv run fastmcp install mcp-json src/mcp_mt5/main.py

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

Files in the repo

Repository payload16 top-level entries
  • .github
  • docs
  • examples
  • src
  • tests
  • .coverage
  • .env.example
  • .gitignore
  • .python-version
  • .readthedocs.yaml
  • CONTRIBUTING.md
  • fastmcp.json
  • pyproject.toml
  • README.md
  • ruff.toml
  • uv.lock

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