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Mcp Server Commands

Mcp Server Commands

Local
github.com/g0t4Developer Tools237Updated 29w ago

About Mcp Server Commands

Mcp Server Commands is an MCP server that runs commands on the host machine and returns their stdout and stderr. It suits users who want a model to carry out command line operations, and it runs locally over STDIO.

Key features

  1. 01Runs commands through the runProcess tool
  2. 02Accepts either a command_line string or an argv array
  3. 03Returns STDOUT and STDERR as text
  4. 04Passes optional stdin to shells and scripts
  5. 05Describes HTTP access through mcpo bridging

Use cases

  1. 01Letting a model query host information such as hostname or ls
  2. 02Sending scripts over stdin to bash or python
  3. 03Performing local file operations from a local model via the command line

MCP support

The project is an MCP server that exposes a run_process tool to MCP clients, executing commands on the host and returning their output. It uses the STDIO transport.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"commands": {
"command": "uvx",
"args": [
"mcpo"
]
}
}
}
Run commanduvx mcpo

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypimcpo

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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

Warning

Be careful what you ask this server to run! In Claude Desktop app, use Approve Once (not Allow for This Chat) so you can review each command, use Deny if you don't trust the command. Permissions are dictated by the user that runs the server. DO NOT run with sudo.

Video walkthrough

YouTube Thumbnail

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

Warning

I briefly used mcpo with open-webui, make sure to vet it for security concerns.

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.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.