remysaissy/mcp-unix-tools

mcp-unix-tools

A local Model Context Protocol (MCP) server that exposes a vast collection of Unix tools to AI models. This server makes it simple and token-efficient for AI assistants to interact with Unix utilities during local development.

Overview

mcp-unix-tools bridges the gap between AI models and Unix command-line tools by implementing the Model Context Protocol. It allows AI assistants to securely execute Unix commands, access system utilities, and perform file operations in a controlled, local environment.

Key Features

• Token-Efficient: Optimized for minimal token usage when communicating with AI models
• Local Execution: All operations run on your local machine for maximum security and privacy
• Modular Design: Each Unix tool is exposed as an independent, testable module
• Type-Safe: Built with Rust for memory safety and reliability
• Extensive Tool Collection: Access to a wide range of Unix utilities through a unified interface

Use Cases

• AI-Assisted Development: Enable AI models to help with file operations, code analysis, and system tasks
• Automated Workflows: Build intelligent automation using AI-driven Unix tool orchestration
• System Administration: Let AI assistants help manage and monitor Unix systems
• DevOps Tasks: Streamline deployment and configuration tasks with AI assistance

Installation

Prerequisites

• Rust toolchain (2024 edition or later)
• Unix-like environment (Linux, macOS, or WSL on Windows)
• cargo, rustfmt, and clippy installed

Building from Source

# Clone the repository
git clone https://github.com/remysaissy/mcp-unix-tools.git
cd mcp-unix-tools

# Build the project
cargo build --release

# The binary will be available at target/release/mcp-unix-tools

Usage

Starting the Server

# Run the MCP server
./target/release/mcp-unix-tools

Connecting AI Clients

Configure your AI client to connect to the MCP server. The server implements the standard Model Context Protocol, making it compatible with any MCP-compliant AI assistant.

Example configuration (adjust based on your AI client):

{
  "mcpServers": {
    "unix-tools": {
      "command": "/path/to/mcp-unix-tools"
    }
  }
}

Development

Project Structure

mcp-unix-tools/
├── src/              # Rust source code
├── openspec/         # Specification and design documents
├── .github/          # GitHub Actions workflows
└── scripts/          # Development helper scripts

Development Scripts

# Format code
./format.sh

# Run linting checks
./check.sh

# Run tests
./test.sh

# Generate coverage report
./coverage.sh

Running Tests

# Run all tests
cargo test

# Run with specific features
cargo test --all-features
cargo test --no-default-features

# Run with coverage
./coverage.sh --lcov --all-features

Code Quality

This project maintains high code quality standards:

• Formatting: Enforced via rustfmt
• Linting: Enforced via clippy with strict settings
• Testing: Comprehensive test coverage required
• Documentation: All public APIs must be documented

Contributing

Contributions are welcome! Please follow these guidelines:

1. Follow the code style: Run ./format.sh before committing
2. Pass all checks: Run ./check.sh to ensure clippy passes
3. Write tests: Maintain high test coverage
4. Document your code: Add documentation for public APIs
5. Use conventional commits: Format commit messages as feat:, fix:, docs:, etc.

For major changes, please open an issue first to discuss the proposed changes.

Architecture

Model Context Protocol

The server implements the Model Context Protocol, an open standard that enables AI models to securely access data and tools. MCP provides:

• Standardized Communication: Consistent interface between AI models and tools
• Security: Controlled access to system resources
• Extensibility: Easy to add new tools and capabilities

Design Principles

• Unix Philosophy: Each tool does one thing well and can be composed
• Modularity: Tools are independently implemented and testable
• Security First: Input validation and sandboxing where appropriate
• Performance: Minimal overhead for tool execution

Security Considerations

Running an MCP server that executes system commands requires careful security considerations:

• Local Only: This server is designed for local development, not remote access
• Input Validation: All inputs are validated before execution
• Sandboxing: Consider running in a containerized environment for additional isolation
• Audit Logs: Monitor server activity in production environments

Warning: Never expose this server to untrusted networks or users without proper authentication and authorization mechanisms.

Roadmap

• Initial tool implementations (file operations, process management, etc.)
• Comprehensive test coverage
• Performance benchmarking and optimization
• Extended tool collection
• Configuration management
• Logging and monitoring capabilities

License

This project is licensed under the Apache License 2.0 - see the file for details.

Acknowledgments

• Model Context Protocol for the specification
• The Rust community for excellent tooling and libraries

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions

Note: This project is currently in early development. APIs and functionality may change as the project evolves.