ezib-mcp 0.1.2

An MCP server built on `ezib_async` that exposes Interactive Brokers' trading and market data functionality.

EZIB-MCP: Interactive Brokers Trading for AI Agents

A Model Context Protocol (MCP) server implementation that enables AI agents to interact with Interactive Brokers' trading platform, providing access to market data, account information, and trading functionality.

Overview

This project provides an MCP server built on ezib_async that allows AI agents to connect to Interactive Brokers, retrieve account information, manage portfolios, and execute trades. It serves as both a practical tool for algorithmic trading and a reference implementation for building MCP servers.

The implementation follows the best practices laid out for building MCP servers, allowing seamless integration with any MCP-compatible client.

Features

The server provides several powerful tools for trading and market data:

1. Account Information: Access account balances, positions, and portfolio data
2. Market Data: Retrieve real-time and historical market data
3. Order Management: Place, modify, and cancel orders
4. Position Management: Monitor and manage trading positions

Prerequisites

• Python 3.11+
• Interactive Brokers TWS or IB Gateway running
• Docker if running the MCP server as a container (recommended)

Installation

Using pip

1. Clone this repository:

   git clone https://github.com/kelvingao/ezib-mcp.git
   cd ezib-mcp
   

2. Install dependencies:

   pip install -e .
   

3. Create a .env file based on .env.example:

   cp .env.example .env
   

4. Configure your environment variables in the .env file (see Configuration section)

Using Docker (Recommended)

1. Build the Docker image:

   docker build -t mcp/ezib --build-arg PORT=8050 .
   

2. Create a .env file based on .env.example and configure your environment variables

Configuration

The following environment variables can be configured in your .env file:

Variable	Description	Default	Example
IB_HOST	Interactive Brokers host	127.0.0.1	127.0.0.1
IB_PORT	Interactive Brokers port	4001	4001
IB_CLIENTID	Client ID for IB connection	0	1
TRANSPORT	Transport protocol (sse or stdio)	-	sse
HOST	Host to bind to when using SSE transport	-	0.0.0.0
PORT	Port to listen on when using SSE transport	-	8050

Running the Server

Using pip

SSE Transport

# Set TRANSPORT=sse in .env then:
python src/server.py

The MCP server will run as an API endpoint that you can connect to with the configuration shown below.

Stdio Transport

With stdio, the MCP client itself can spin up the MCP server, so nothing to run at this point.

Using Docker

SSE Transport

docker run --env-file .env -p 8050:8050 mcp/ezib

The MCP server will run as an API endpoint within the container that you can connect to with the configuration shown below.

Stdio Transport

With stdio, the MCP client itself can spin up the MCP server container, so nothing to run at this point.

Integration with MCP Clients

SSE Configuration

Once you have the server running with SSE transport, you can connect to it using this configuration:

{
  "mcpServers": {
    "ezib": {
      "transport": "sse",
      "url": "http://localhost:8050/sse"
    }
  }
}

Note for Windsurf users: Use serverUrl instead of url in your configuration:

{
  "mcpServers": {
    "ezib": {
      "transport": "sse",
      "serverUrl": "http://localhost:8050/sse"
    }
  }
}

Note for n8n users: Use host.docker.internal instead of localhost since n8n has to reach outside of its own container to the host machine:

So the full URL in the MCP node would be: http://host.docker.internal:8050/sse

Make sure to update the port if you are using a value other than the default 8050.

Python with Stdio Configuration

Add this server to your MCP configuration for Claude Desktop, Windsurf, or any other MCP client:

{
  "mcpServers": {
    "ezib": {
      "command": "your/path/to/ezib-mcp/.venv/bin/python",
      "args": ["your/path/to/ezib-mcp/src/main.py"],
      "env": {
        "TRANSPORT": "stdio"
      }
    }
  }
}

Docker with Stdio Configuration

{
  "mcpServers": {
    "ezib": {
      "command": "docker",
      "args": ["run", "--rm", "-i", 
               "-e", "TRANSPORT", 
               "mcp/ezib"],
      "env": {
        "TRANSPORT": "stdio"
      }
    }
  }
}

Usage Examples

Here are some examples of how to use the EZIB MCP server with an AI agent:

Getting Account Information

Retrieve my current account balance and positions.

Placing an Order

Place a market order to buy 100 shares of AAPL.

Retrieving Market Data

Get the current price and trading volume for TSLA.

Managing Positions

Show me all my open positions and their current P&L.

License

MIT License