# qontinui-mcp
Lightweight MCP server for [Qontinui Runner](https://github.com/qontinui/qontinui-runner) - enables AI-driven visual automation.
## Installation
```bash
pip install qontinui-mcp
```
## Quick Start
1. **Start the Qontinui Runner** (desktop application)
2. **Configure your AI client** (Claude Desktop, Claude Code, Cursor, etc.)
Add to your MCP configuration:
```json
{
"mcpServers": {
"qontinui": {
"command": "qontinui-mcp",
"args": []
}
}
}
```
3. **Run workflows via AI**
The AI can now:
- Load workflow configuration files
- Run visual automation workflows
- Monitor execution status
- Control which monitor to use
## Configuration
Environment variables:
| Variable | Description | Default |
|----------|-------------|---------|
| `QONTINUI_RUNNER_HOST` | Runner host address | Auto-detected (WSL-aware) |
| `QONTINUI_RUNNER_PORT` | Runner HTTP port | `9876` |
## Available Tools
| Tool | Description |
|------|-------------|
| `get_executor_status` | Get runner status |
| `list_monitors` | List available monitors |
| `load_config` | Load a workflow configuration file |
| `ensure_config_loaded` | Load config if not already loaded |
| `get_loaded_config` | Get loaded configuration info |
| `run_workflow` | Run a workflow by name |
| `stop_execution` | Stop current execution |
## Example Usage
```python
# In an AI conversation:
"Load the config at /path/to/workflow.json and run the 'login_test' workflow on the left monitor"
```
## Development
```bash
# Clone
git clone https://github.com/qontinui/qontinui-mcp
cd qontinui-mcp
# Install dependencies
poetry install
# Run server locally
poetry run qontinui-mcp
```
## License
MIT
