ibkr-mcp-server
# IBKR MCP Server
A professional Model Context Protocol (MCP) server for Interactive Brokers API integration, designed for use with Claude Desktop and Claude Code.
[](https://github.com/yourusername/ibkr-mcp-server/actions/workflows/ci.yml)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
## Features
- ✅ **Multi-Account Support** - Switch between multiple IBKR accounts
- ✅ **Short Selling Analysis** - Shortable shares, borrow rates, margin requirements
- ✅ **Real-time Market Data** - Live quotes, historical data, options chains
- ✅ **Portfolio Management** - Positions, P&L, account summaries
- ✅ **Trading Operations** - Place, modify, cancel orders (with safety checks)
- ✅ **Auto-Reconnection** - Handles TWS/Gateway restarts gracefully
- ✅ **Production Ready** - Proper error handling, logging, and monitoring
## Quick Start
### Prerequisites
- Python 3.10 or higher
- Interactive Brokers account with TWS or IB Gateway
- Claude Desktop or Claude Code
### Installation
1. **Clone the repository:**
```bash
git clone https://github.com/yourusername/ibkr-mcp-server.git
cd ibkr-mcp-server
```
2. **Run the setup script:**
```bash
# macOS/Linux
chmod +x scripts/setup.sh
./scripts/setup.sh
# Windows
scripts\setup.bat
```
3. **Configure your settings:**
```bash
cp .env.example .env
# Edit .env with your IBKR settings
```
4. **Start TWS/IB Gateway** and enable API connections
5. **Test the server:**
```bash
python -m ibkr_mcp_server.main --test
```
### Claude Integration
**Claude Desktop:**
Add to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"ibkr": {
"command": "python",
"args": ["-m", "ibkr_mcp_server.main"],
"cwd": "/path/to/ibkr-mcp-server"
}
}
}
```
**Claude Code:**
```bash
claude mcp add ibkr 'python -m ibkr_mcp_server.main' --cwd /path/to/ibkr-mcp-server
```
## Usage Examples
### Basic Operations
```python
# Get portfolio across all accounts
"Show me my current portfolio"
# Switch accounts
"Switch to account DU7654321"
# Market data
"Get real-time quotes for AAPL, TSLA, MSFT"
```
### Short Selling Analysis
```python
# Complete short selling analysis
"Analyze short selling for GME, AMC, BBBY - show availability, borrow costs, and margin requirements"
# Check specific account
"Check shortable shares for TSLA in my paper trading account"
```
### Trading Operations
```python
# Place orders (paper trading recommended)
"Place a limit order to buy 100 shares of AAPL at $150"
# Check margin requirements
"What are the margin requirements for shorting 200 shares of TSLA?"
```
## Available Tools
| Tool | Description |
|------|-------------|
| `get_portfolio` | Current portfolio positions and P&L |
| `get_account_summary` | Account balances and key metrics |
| `switch_account` | Switch between IBKR accounts |
| `check_shortable_shares` | Short selling availability |
| `get_margin_requirements` | Margin requirements for securities |
| `get_borrow_rates` | Stock borrow rates (short selling costs) |
| `short_selling_analysis` | Complete short selling analysis |
| `get_market_data` | Real-time market quotes |
| `get_historical_data` | Historical price data |
| `place_order` | Place trading orders (with safety checks) |
| `get_connection_status` | Check IBKR connection status |
## Configuration
### Environment Variables
```env
# IBKR Connection
IBKR_HOST=127.0.0.1
IBKR_PORT=7497 # 7497=TWS Paper, 7496=TWS Live, 4001=Gateway
IBKR_CLIENT_ID=1
IBKR_IS_PAPER=true
# Logging
LOG_LEVEL=INFO
# Safety
ENABLE_LIVE_TRADING=false # Set to true for live trading
MAX_ORDER_SIZE=1000 # Maximum order size
```
### TWS/Gateway Setup
1. Start TWS or IB Gateway
2. Go to Configuration → API → Settings
3. Enable "ActiveX and Socket Clients"
4. Set socket port (7497 for paper, 7496 for live)
5. Add 127.0.0.1 to "Trusted IPs"
6. Check "Download open orders on connection"
## Development
### Setup Development Environment
```bash
pip install -e ".[dev]"
pre-commit install
```
### Running Tests
```bash
pytest tests/ -v
```
### Code Quality
```bash
black ibkr_mcp_server/
isort ibkr_mcp_server/
mypy ibkr_mcp_server/
```
## Deployment
### Auto-start on Boot (macOS)
```bash
python scripts/install_service.py --platform macos
```
### Auto-start on Boot (Linux)
```bash
python scripts/install_service.py --platform linux
```
### Docker Deployment
```bash
docker build -t ibkr-mcp-server .
docker run -d --name ibkr-mcp -p 8080:8080 ibkr-mcp-server
```
## Documentation
- [API Reference](docs/API.md)
- [Deployment Guide](docs/DEPLOYMENT.md)
- [Troubleshooting](docs/TROUBLESHOOTING.md)
## Safety & Disclaimers
⚠️ **Important Safety Notes:**
- Always test with paper trading first
- Verify all data in TWS before making trading decisions
- This software is for educational purposes
- Use at your own risk
- No warranty provided
## Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request
## License
MIT License - see [LICENSE](LICENSE) file for details.
## Support
- [Issues](https://github.com/yourusername/ibkr-mcp-server/issues)
- [Discussions](https://github.com/yourusername/ibkr-mcp-server/discussions)
- [Wiki](https://github.com/yourusername/ibkr-mcp-server/wiki)
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: check_shortable_shares vs short_selling_analysis are differentiated by scope (single check vs comprehensive analysis); get_accounts vs get_account_summary vs get_portfolio cover different account aspects; get_connection_status and switch_account are unique. No significant overlap.
Tools follow a consistent snake_case naming pattern with verb_noun structure (e.g., get_account_summary, get_portfolio). One exception is short_selling_analysis which is noun_verb but still readable and fits the pattern.
8 tools is appropriate for the domain of financial account information and short selling analysis. Not excessive, and each tool contributes a distinct function without unnecessary duplication.
The server covers account information, portfolio, margin, and short selling analysis, but lacks essential trading operations like order placement, modification, or market data retrieval. The surface is focused on analysis and account management, leaving a notable gap for execution.