Loading...
iTerm-MCP allows models to interact with and control iTerm2, enabling automation and screen inspection, but requires careful monitoring due to potential risks.
Boost this tool
Subscribe to listing upgrades or segmented pushes.
iTerm-MCP allows models to interact with and control iTerm2, enabling automation and screen inspection, but requires careful monitoring due to potential risks.
iTerm-MCP offers powerful terminal interaction capabilities but poses significant risks due to the lack of command restrictions and potential for unexpected model behavior. It's reasonably safe for experienced users who closely monitor model actions and understand terminal commands, but risky for novice users or unsupervised environments.
Performance depends on the speed of command execution and the amount of terminal output. Long-running commands may impact responsiveness.
Cost is primarily related to the resources consumed by the commands executed in the terminal (e.g., CPU, memory, network).
npx -y @smithery/cli install iterm-mcp --client claude{
"mcpServers": {
"iterm-mcp": {
"command": "npx",
"args": [
"-y",
"iterm-mcp"
]
}
}
}write_to_terminalWrites a command to the active iTerm terminal and executes it.
Unrestricted command execution can have significant consequences.
read_terminal_outputReads a specified number of lines from the active iTerm terminal.
Read-only operation with no side effects.
send_control_characterSends a control character (e.g., Ctrl+C) to the active iTerm terminal.
Can interrupt processes or alter terminal behavior.
None
local
iTerm-MCP offers powerful terminal interaction capabilities but poses significant risks due to the lack of command restrictions and potential for unexpected model behavior. It's reasonably safe for experienced users who closely monitor model actions and understand terminal commands, but risky for novice users or unsupervised environments.
The model has full control over the iTerm terminal, so careful monitoring and task definition are crucial to prevent unintended actions.
Production Tip
Start with small, focused tasks and gradually increase complexity as you gain confidence in the model's behavior.
Monitor the model's activity closely, start with small tasks, and be prepared to abort if it goes off track. Avoid running sensitive commands or exposing sensitive data in the terminal.
Yes, if the model executes commands that access the file system. Exercise caution when granting the model access to the terminal.
It interacts with the active iTerm terminal, so ensure the correct window/tab is active before delegating tasks.
Use the MCP Inspector for debugging, as described in the documentation.
You may need to interrupt the model or manually terminate the command in the terminal.
Use with caution in production environments. Thoroughly test and monitor the model's behavior before deploying it in a production setting.
No built-in logging is provided. Logging would depend on the commands executed in the terminal.