MCPTools: The Swiss Army Knife for MCP Servers That's Revolutionizing AI Development Workflows

In the rapidly evolving landscape of AI development, the Model Context Protocol (MCP) has emerged as a game-changing standard for connecting AI assistants with external tools and data sources. But working with MCP servers has traditionally required complex integrations and custom implementations. Enter MCPTools – a comprehensive command-line interface that's transforming how developers interact with MCP servers, making it as simple as running a single command.

Built by GitHub Star Fatih Kadir Akin (who also created GitHub Copilot's prompts feature), MCPTools has quickly gained traction with over 1,300 stars and is being recognized as one of the top 10 new open source AI projects on GitHub.

What Makes MCPTools Special?

MCPTools isn't just another CLI tool – it's a complete ecosystem for MCP development that addresses every aspect of working with MCP servers:

• Universal Compatibility: Works with any MCP-compatible server using multiple transport methods (HTTP, stdio, SSE)
• Developer-Friendly: Intuitive commands with beautiful, colorized output formats
• Extensible Architecture: Create mock servers, proxy requests to shell scripts, and scaffold new projects
• Security-First: Built-in guard mode for restricting access to sensitive operations
• Production Ready: Comprehensive logging, configuration management, and web interface

Getting Started: Installation and Basic Usage

Getting MCPTools up and running is straightforward, with multiple installation options to suit your environment:

Installation Options

For macOS users (Homebrew):

brew tap f/mcptools
brew install mcp

For Windows and Linux (from source):

go install github.com/f/mcptools/cmd/mcptools@latest

The binary is installed as mcp on macOS and mcptools on other platforms, with convenient aliases available.

Your First MCP Interaction

Let's start with a simple example using the filesystem server:

# List all available tools from a filesystem server
mcp tools npx -y @modelcontextprotocol/server-filesystem ~

# Call a specific tool to read a file
mcp call read_file --params '{"path":"README.md"}' npx -y @modelcontextprotocol/server-filesystem ~

# Open an interactive shell for exploration
mcp shell npx -y @modelcontextprotocol/server-filesystem ~

The output is beautifully formatted in a man-page style with color coding:

read_file(path:str)
     Read the complete contents of a file from the file system.
read_multiple_files(paths:str[])
     Read the contents of multiple files simultaneously.
list_dir(path:str)
     Lists the contents of a directory.

Advanced Features That Set MCPTools Apart

1. Multiple Transport Methods

MCPTools supports three different transport methods, automatically detecting the appropriate one:

Stdio Transport (for command-line tools):

mcp tools npx -y @modelcontextprotocol/server-filesystem ~

HTTP SSE Transport (for legacy servers):

mcp tools http://localhost:3001/sse

Streamable HTTP Transport (modern, recommended):

mcp tools https://api.example.com/mcp

2. Interactive Shell Mode

The interactive shell provides a persistent session for exploring MCP servers:

mcp shell npx -y @modelcontextprotocol/server-filesystem ~

Inside the shell, you can:

• List tools, resources, and prompts
• Call functions directly with JSON parameters
• Switch output formats on the fly
• Access help and documentation

3. Web Interface for Visual Interaction

For those who prefer a graphical interface, MCPTools includes a built-in web server:

# Start web interface on default port (41999)
mcp web npx -y @modelcontextprotocol/server-filesystem ~

# Use custom port
mcp web --port 8080 docker run -i --rm -e GITHUB_PERSONAL_ACCESS_TOKEN ghcr.io/github/github-mcp-server

The web interface features:

• Sidebar listing all available tools, resources, and prompts
• Form-based and JSON-based parameter editing
• Formatted response views
• Interactive parameter forms with automatic validation

Server Modes: Extending MCP Functionality

Mock Server Mode

Perfect for testing and development, the mock server creates simulated MCP servers:

# Create a simple mock server
mcp mock tool hello_world "A simple greeting tool"

# Create complex mock with multiple entity types
mcp mock tool hello_world "A greeting tool" \
       prompt welcome "A welcome prompt" "Hello {{name}}, welcome to {{location}}!" \
       resource docs://readme "Documentation" "Mock MCP Server\nThis is a mock server"

Proxy Mode: Shell Script Integration

One of MCPTools' most powerful features is the ability to turn shell scripts into MCP tools:

# Register a shell script as an MCP tool
mcp proxy tool add_operation "Adds a and b" "a:int,b:int" ./examples/add.sh

# Register an inline command
mcp proxy tool add_operation "Adds a and b" "a:int,b:int" -e 'echo "total is $a + $b = $(($a+$b))"'

# Start the proxy server
mcp proxy start

Example shell script (add.sh):

#!/bin/bash
if [ -z "$a" ] || [ -z "$b" ]; then
  echo "Error: Missing required parameters 'a' or 'b'"
  exit 1
fi
result=$(($a + $b))
echo "The sum of $a and $b is $result"

Guard Mode: Security and Access Control

Guard mode provides fine-grained access control for production environments:

# Allow only file reading operations
mcp guard --allow 'tools:read_*' --deny 'tools:write_*,create_*,delete_*' npx -y @modelcontextprotocol/server-filesystem ~

# Permit only specific tools
mcp guard --allow 'tools:search_files' npx -y @modelcontextprotocol/server-filesystem ~

Configuration Management and Aliases

Server Aliases

Save frequently used server configurations:

# Add a server alias
mcp alias add myfs npx -y @modelcontextprotocol/server-filesystem ~/

# Use the alias
mcp tools myfs
mcp call read_file --params '{"path":"README.md"}' myfs

LLM Apps Config Management

MCPTools can manage MCP configurations across multiple applications:

# Scan for existing configurations
mcp configs scan

# Add server to multiple applications at once
mcp configs set vscode,cursor,claude-desktop my-server npm run mcp-server

# Add GitHub MCP Server to multiple IDEs
mcp configs set windsurf,cursor,vscode GitHub \
  --env "GITHUB_PERSONAL_ACCESS_TOKEN=github_pat_xxx" \
  docker run -i --rm -e GITHUB_PERSONAL_ACCESS_TOKEN ghcr.io/github/github-mcp-server

Project Scaffolding: Rapid Development

MCPTools includes powerful scaffolding capabilities for creating new MCP servers:

# Create a new MCP project
mkdir my-mcp-server && cd my-mcp-server

# Scaffold with specific components
mcp new tool:calculate resource:file prompt:greet

# Choose transport type
mcp new tool:calculate --transport=stdio
mcp new tool:calculate --transport=sse

# Install and test
npm install && npm run build
mcp tools node build/index.js

Output Formats and Debugging

MCPTools supports multiple output formats to suit different needs:

# Table format (default) - colorized, human-readable
mcp tools npx -y @modelcontextprotocol/server-filesystem ~

# JSON format - compact
mcp tools --format json npx -y @modelcontextprotocol/server-filesystem ~

# Pretty JSON format - indented
mcp tools --format pretty npx -y @modelcontextprotocol/server-filesystem ~

For debugging, comprehensive logging is available:

# View server logs during operations
mcp tools --server-logs npx -y @modelcontextprotocol/server-filesystem ~

# Monitor proxy server logs
tail -f ~/.mcpt/logs/proxy.log

# Monitor mock server logs
tail -f ~/.mcpt/logs/mock.log

Real-World Use Cases

1. Development and Testing

Use mock servers to test AI applications without complex backend setup:

# Create a comprehensive mock for testing
mcp mock tool file_search "Search files" \
       tool file_read "Read file contents" \
       resource config://app "App configuration" \
       prompt system_prompt "System instructions"

2. Legacy System Integration

Convert existing shell scripts and command-line tools into MCP-compatible services:

# Convert a backup script to MCP tool
mcp proxy tool backup_database "Backup database" "db_name:string" ./scripts/backup.sh

# Convert a monitoring script
mcp proxy tool check_system "System health check" "" -e 'df -h && free -m && uptime'

3. Secure Production Deployments

Use guard mode to create secure, limited-access MCP servers:

# Read-only filesystem access for AI assistants
mcp guard --deny 'tools:write_*,delete_*,create_*,move_*' npx -y @modelcontextprotocol/server-filesystem /safe/directory

Performance and Architecture

MCPTools is built with Go, providing excellent performance characteristics:

• Fast startup: Sub-second initialization for most operations
• Low memory footprint: Efficient resource usage even with multiple concurrent connections
• Concurrent processing: Handle multiple MCP requests simultaneously
• Robust error handling: Comprehensive error reporting and recovery

The architecture supports:

• Session management for stateful connections
• Automatic transport detection and fallback
• Streaming responses for large data transfers
• Configurable timeouts and retry logic

Community and Ecosystem

MCPTools has rapidly built a strong community:

• 1,300+ GitHub stars and growing
• 89 forks with active contributions
• 13 contributors including AI assistants (Claude, GitHub Copilot)
• MIT license ensuring open source compatibility

The project is actively maintained with regular releases and responsive issue handling.

Future Roadmap

The MCPTools roadmap includes exciting upcoming features:

• Authentication support: Secure authentication mechanisms for production deployments
• Enhanced web interface: More interactive features and better UX
• Plugin system: Extensible architecture for custom functionality
• Performance optimizations: Even faster operations and lower resource usage

Getting Involved

MCPTools welcomes contributions from the community:

• GitHub Repository: https://github.com/f/mcptools
• Issues and Feature Requests: Use GitHub Issues for bug reports and feature requests
• Contributing Guidelines: Comprehensive guide available in the repository
• Blog Post: Detailed comparison with MCP Inspector

Conclusion: The Future of MCP Development

MCPTools represents a significant leap forward in MCP development tooling. By providing a comprehensive, user-friendly interface for every aspect of MCP server interaction, it's lowering the barrier to entry for AI developers while providing the advanced features needed for production deployments.

Whether you're building your first MCP integration, testing AI applications, or deploying production systems, MCPTools provides the tools you need to succeed. Its combination of simplicity for beginners and power for experts makes it an essential tool in any AI developer's toolkit.

The project's rapid adoption and active development community suggest that MCPTools will continue to evolve and improve, potentially becoming the de facto standard for MCP development workflows.

Ready to revolutionize your MCP development workflow? Install MCPTools today and experience the difference that proper tooling can make in your AI development projects.

For more expert insights and tutorials on AI and automation, visit us at decisioncrafters.com.