Enables configuration management automation by allowing AI agents to execute Ansible commands for infrastructure provisioning and application deployment
Provides HTTP request capabilities, allowing AI agents to make web requests, test APIs, and retrieve web content from various endpoints
Enables container operations management, allowing AI agents to control Docker containers, images, and container lifecycle operations
Provides media processing capabilities, enabling AI agents to convert, manipulate, and process audio and video files using FFmpeg commands
Enables Kubernetes package management, allowing AI agents to deploy, upgrade, and manage applications in Kubernetes clusters using Helm charts
Provides Kubernetes cluster management capabilities, enabling AI agents to deploy, scale, and manage containerized applications and cluster resources using kubectl commands
Serves as the runtime environment for the MCP-Ables server, enabling the execution of shell commands through Python-based MCP tools
Enables infrastructure as code management, allowing AI agents to provision, modify, and destroy cloud infrastructure resources using Terraform commands
Uses YAML configuration files to define shell command mappings, enabling users to create MCP tools by writing simple YAML specifications instead of coding
MCP-Ables
Turn any shell command into MCP Server
Why bother coding long MCP servers for every need, when you can just provide shell commands?
What is MCP-Ables?
MCP-Ables bridges the gap between command-line tools and AI agents like Claude Code. Write a tiny YAML file describing your shell command, and MCP-Ables automatically generates an MCP (Model Context Protocol) server that AI agents can call.
No Python coding. No complex setup. Just YAML → MCP → AI-callable tools.
Quick Start
Prerequisites
Python 3.11+
The command-line tool you want to expose (e.g.,
nuclei
,ls
, etc.)
Installation
Usage
Create a YAML file describing your tool(s) (see examples below)
Run MCP-Ables with a file or directory:
# Single file python mcpables-main.py examples/nuclei.yaml # Directory (scans recursively for .yaml/.yml files) python mcpables-main.py examples/The MCP server 'mcpables' is now running with all your tools!
Claude Desktop Integration
Connect MCP-Ables to Claude Desktop so AI can use your tools directly from chat.
Configuration
Locate Claude Desktop config file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
Linux:
~/.config/Claude/claude_desktop_config.json
Windows:
%APPDATA%\Claude\claude_desktop_config.json
Add MCP-Ables server:
Restart Claude Desktop - Tools will automatically appear
Configuration Examples
Single file (specific vibe):
Directory (all tools):
Multiple configurations (different vibes):
Verify Connection
After restarting Claude Desktop, you can verify the tools are available:
Type a message asking Claude about available tools
Tools will appear with names like
nuclei_scan
,nmap_scan
, etc.Claude can now execute commands directly!
Use Cases
🔐 SecOps Vibes
Run security scanners from AI agents:
Nuclei - Vulnerability scanning
Nmap - Network discovery
Subfinder - Subdomain enumeration
Amass - Attack surface mapping
🎯 Hacking Vibes
Integrate pentesting tools:
SQLMap - SQL injection testing
Hydra - Password brute forcing
Gobuster - Directory/DNS brute forcing
Nikto - Web server scanning
🚀 DevOps Vibes
Automate infrastructure from chat:
kubectl - Kubernetes management
terraform - Infrastructure as code
ansible - Configuration management
helm - K8s package management
🖥️ SysAdmin Vibes
Server management via AI:
systemctl - Service control
docker - Container operations
journalctl - Log viewing
iptables - Firewall rules
🌐 NetOps Vibes
Network diagnostics:
ping - Connectivity testing
traceroute - Path tracing
dig - DNS queries
whois - Domain info
📊 Data Vibes
CLI data processing:
jq - JSON processing
curl - HTTP requests
grep/awk - Text processing
ffmpeg - Media conversion
YAML Schema
See examples/
Single-Tool Format
Multi-Tool Format
Define multiple tools in one YAML file:
Argument Fields
type: Data type (
string
,int
,float
,bool
)description: Human-readable explanation for AI agents to understand usage
required: Whether the argument must be provided (
true
orfalse
)default: Default value if not provided (only for optional arguments)
Examples
Simple Echo
examples/echo.yaml:
Run it:
Nuclei Scanner
examples/nuclei.yaml:
Multi-Tool Example
examples/security-tools.yaml:
Run it:
Directory Example
Organize tools in separate files:
Run all tools from directory:
Roadmap
Phase 1 (Completed):
✓ YAML → MCP conversion
✓ Shell command execution
✓ Argument validation and defaults
✓ Rich descriptions for AI agents
✓ Multi-tool YAML support
✓ Directory scanning for YAML files
Phase 2 (Future):
Sandboxing and isolation
Resource limits (CPU, memory, timeout)
Audit logging
HTTP request support
Multi-command workflows
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.
Turns any shell command into an MCP server by defining command-line tools in simple YAML files. Enables AI agents to execute system commands, security scanners, DevOps tools, and CLI utilities directly from chat interfaces.