Execute Terminal Commands via LLM

runProcess tool

The runProcess tool runs processes on the host machine. There are two mutually exclusive ways to invoke it:

1. command_line (string) - Executed via the system's default shell (just like typing into bash/fish/pwsh/etc). Shell features like pipes, redirects, and variable expansion all work.
2. argv (string array) - Direct executable invocation. argv[0] is the executable, the rest are arguments. No shell interpretation.

You cannot pass both. The tool infers whether to use a shell from which parameter you provide.

If you want your model to use specific shell(s) on a system, I would list them in your system prompt. Or, maybe in your tool instructions, though models tend to pay better attention to examples in a system prompt.

Let me know if you encounter problems!

Tools

Tools are for LLMs to request. Claude Sonnet 3.5 intelligently uses run_process. And, initial testing shows promising results with Groq Desktop with MCP and llama4 models.

Currently, just one command to rule them all!

• run_process - run a command, i.e. hostname or ls -al or echo "hello world" etc
  • Returns STDOUT and STDERR as text
  • Optional stdin parameter means your LLM can
    • pass scripts over STDIN to commands like fish, bash, zsh, python
    • create files with cat >> foo/bar.txt from the text in stdin

Video walkthrough

Prompts

Prompts are for users to include in chat history, i.e. via Zed's slash commands (in its AI Chat panel)

• run_process - generate a prompt message with the command output

• FYI this was mostly a learning exercise... I see this as a user requested tool call. That's a fancy way to say, it's a template for running a command and passing the outputs to the model!

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

Groq Desktop (beta, macOS) uses ~/Library/Application Support/groq-desktop-app/settings.json

Use the published npm package

Published to npm as mcp-server-commands using this workflow

{
  "mcpServers": {
    "mcp-server-commands": {
      "command": "npx",
      "args": ["mcp-server-commands"]
    }
  }
}

Use a local build (repo checkout)

Make sure to run npm run build

{
  "mcpServers": {
    "mcp-server-commands": {
      // works b/c of shebang in index.js
      "command": "/path/to/mcp-server-commands/build/index.js"
    }
  }
}

Local Models

• Most models are trained such that they don't think they can run commands for you.
  • Sometimes, they use tools w/o hesitation... other times, I have to coax them.
  • Use a system prompt or prompt template to instruct that they should follow user requests. Including to use run_processs without double checking.
• Ollama is a great way to run a model locally (w/ Open-WebUI)

# NOTE: make sure to review variants and sizes, so the model fits in your VRAM to perform well!

# Probably the best so far is [OpenHands LM](https://www.all-hands.dev/blog/introducing-openhands-lm-32b----a-strong-open-coding-agent-model)
ollama pull https://huggingface.co/lmstudio-community/openhands-lm-32b-v0.1-GGUF

# https://ollama.com/library/devstral
ollama pull devstral

# Qwen2.5-Coder has tool use but you have to coax it
ollama pull qwen2.5-coder

HTTP / OpenAPI

The server is implemented with the STDIO transport.
For HTTP, use mcpo for an OpenAPI compatible web server interface.
This works with Open-WebUI

uvx mcpo --port 3010 --api-key "supersecret" -- npx mcp-server-commands

# uvx runs mcpo => mcpo run npx => npx runs mcp-server-commands
# then, mcpo bridges STDIO <=> HTTP

Logging

Claude Desktop app writes logs to ~/Library/Logs/Claude/mcp-server-mcp-server-commands.log

By default, only important messages are logged (i.e. errors).
If you want to see more messages, add --verbose to the args when configuring the server.

By the way, logs are written to STDERR because that is what Claude Desktop routes to the log files.
In the future, I expect well formatted log messages to be written over the STDIO transport to the MCP client (note: not Claude Desktop app).

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.