CLI

## `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](https://github.com/groq/groq-desktop-beta) 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 <a href="https://youtu.be/0-VPu1Pc18w"><img src="https://img.youtube.com/vi/0-VPu1Pc18w/maxresdefault.jpg" width="480" alt="YouTube Thumbnail"></a> ## 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: ```bash npm install ``` Build the server: ```bash npm run build ``` For development with auto-rebuild: ```bash 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](https://www.npmjs.com/package/mcp-server-commands) using this [workflow](https://github.com/g0t4/mcp-server-commands/actions) ```json { "mcpServers": { "mcp-server-commands": { "command": "npx", "args": ["mcp-server-commands"] } } } ``` ### Use a local build (repo checkout) Make sure to run `npm run build` ```json { "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) ```sh # 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`](https://github.com/open-webui/mcpo) for an `OpenAPI` compatible web server interface. This works with [`Open-WebUI`](https://github.com/open-webui/open-webui) ```bash 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](https://github.com/modelcontextprotocol/inspector), which is available as a package script: ```bash npm run inspector ``` The Inspector will provide a URL to access debugging tools in your browser.