CCM
/MCP
SkillsMCPMarketplacesDigestLearnAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Claude Code Marketplaces

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Plugins Reference

Community

  • About
  • Learn
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

MCP Commands Server

g0t4/mcp-server-commands
224
Summary

The mcp-server-commands server provides LLMs with a `run_process` tool that executes system commands on the host machine either through shell interpretation (via `command_line` parameter) or direct executable invocation (via `argv` array), returning standard output and standard error as text. It supports an optional `stdin` parameter enabling LLMs to pipe scripts to interpreters like bash or Python, and pass file creation commands. The server solves the problem of allowing AI models to execute arbitrary commands and interact with the host system through a standardized interface, though it requires explicit user approval for each command execution to mitigate security risks.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Vibe Prospecting MCPVibe Prospecting MCP
Vibe Prospecting MCP
Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Vibe Prospecting MCPVibe Prospecting MCP
Vibe Prospecting MCP
Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →

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.

Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Vibe Prospecting MCPVibe Prospecting MCP
Vibe Prospecting MCP
Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
UpdatedMar 7, 2026
View on GitHub