Supports containerized deployment for secure isolation of shell command execution
Supports command execution on Unix-like systems including Linux
Supports command execution on macOS operating system
Provides secure shell command execution capabilities with configurable security constraints, command validation, and execution limits
mcp-shell 🐚
A robust Model Context Protocol (MCP) server that provides secure shell command execution capabilities to AI assistants and other MCP clients. In other words: the brain thinks, this runs the commands.
🧠💥🖥️ Think of
mcp-shell
as the command-line actuator for your LLM. While language models reason about the world,mcp-shell
is what lets them touch it.
What is this?
This tool creates a bridge between AI systems and your shell environment through the standardized MCP protocol. It exposes the system shell as a structured tool, enabling autonomous workflows, tool-assisted reasoning, and real-world problem solving.
Built on top of the official MCP SDK for Go: mark3labs/mcp-go.
It's written in Go, integrates directly with mcp-go
, and provides a clean path from thought to execution. I'm aware similar projects exist — this one’s mine. It solves the problem the way I want it solved: minimal, composable, auditable.
Out of the box it runs isolated via Docker, but that's just a start. The roadmap includes support for optional jailing mechanisms like chroot
, namespaces, and syscall-level confinement — without depending on Docker for everything.
Features
- 🔒 Security First: Configurable command allowlists, blocklists, and execution constraints
- 🐳 Docker Ready: Lightweight Alpine-based container for secure isolation
- 📊 Structured Responses: JSON-formatted output with stdout, stderr, exit codes, and execution metadata
- 🔄 Binary Data Support: Optional base64 encoding for handling binary command output
- ⚡ Performance Monitoring: Execution time tracking and resource limits
- 📋 Audit Logging: Complete command execution audit trail with structured logging
- 🎯 Context Aware: Supports command execution with proper context cancellation
- ⚙️ Environment Configuration: Full configuration via environment variables
Security Features
- Command Validation: Allowlist/blocklist with regex pattern matching
- Execution Limits: Configurable timeouts and output size limits
- User Isolation: Run commands as unprivileged users
- Working Directory: Restrict execution to specific directories
- Audit Trail: Complete logging of all command executions
- Resource Limits: Memory and CPU usage constraints
Quick Start
Prerequisites
- Go 1.23 or later
- Unix-like system (Linux, macOS, WSL)
- Docker (optional, for containerized deployment)
Installation
Basic Usage
Docker Deployment (Recommended)
Configuration
Environment Variables
Basic server and logging configuration via environment variables:
Server Configuration
MCP_SHELL_SERVER_NAME
: Server name (default: "mcp-shell 🐚")MCP_SHELL_VERSION
: Server version (set at compile time)
Logging Configuration
MCP_SHELL_LOG_LEVEL
: Log level (debug, info, warn, error, fatal)MCP_SHELL_LOG_FORMAT
: Log format (json, console)MCP_SHELL_LOG_OUTPUT
: Log output (stdout, stderr, file)
Configuration File
MCP_SHELL_SEC_CONFIG_FILE
: Path to YAML configuration file
Security Configuration (YAML Only)
Security settings are configured exclusively via YAML configuration file:
Example security configuration file:
Tool Parameters
command
(string, required): Shell command to executebase64
(boolean, optional): Return stdout/stderr as base64-encoded strings
Response Format
Integration Examples
With Claude Desktop
Production Deployment
Development
Security Considerations
⚠️ Important Security Notes
- Default Mode: Runs with full system access when security is disabled (which is, of course, a terrible idea — unless you're into that).
- Container Isolation: Use Docker deployment for additional security layers
- User Privileges: Run as non-root user in production
- Network Access: Commands can access network unless explicitly restricted
- File System: Can read/write files based on user permissions
Recommended Production Setup
Create security.yaml
:
Set environment:
Contributing
- Fork the repository
- Create feature branch (
git checkout -b feature/amazing-feature
) - Commit changes (
git commit -m 'Add amazing feature'
) - Push to branch (
git push origin feature/amazing-feature
) - Open Pull Request
Ensure code is formatted (make fmt
) and passes tests (make test
).
License
MIT License - See LICENSE file for details.
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
Give hands to AI. MCP server to run shell commands securely, auditably, and on demand.
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