CMD Executor▌
by phialsbasement
CMD Executor: Cross-platform MCP server to run command-line operations and SSH on Windows and Linux through a standardiz
Cross-platform MCP server for executing command-line operations and SSH connections on Windows and Linux systems through a standardized interface.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / System administrators managing servers
- / Developers automating deployment scripts
- / DevOps teams running remote operations
- / IT professionals performing system maintenance
capabilities
- / Execute CMD commands on Windows and Linux
- / Establish SSH connections to remote servers
- / Run terminal operations through MCP protocol
- / Manage cross-platform command execution
- / Interface with system administration tasks
what it does
Executes command-line operations and SSH connections on Windows and Linux systems through a standardized MCP interface. Allows AI assistants to run terminal commands and manage remote servers.
about
CMD Executor is a community-built MCP server published by phialsbasement that provides AI assistants with tools and capabilities via the Model Context Protocol. CMD Executor: Cross-platform MCP server to run command-line operations and SSH on Windows and Linux through a standardiz It is categorized under developer tools.
how to install
You can install CMD Executor in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
CMD Executor is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
CMD MCP Server
A Model Context Protocol (MCP) server implementation for executing CMD commands on both Windows and Linux, as well as allowing SSH connections. This server allows you to integrate command-line operations with MCP-compatible applications.
<a href="https://glama.ai/mcp/servers/s83mqs6123"><img width="380" height="200" src="https://glama.ai/mcp/servers/s83mqs6123/badge" alt="cmd-mcp-server MCP server" /></a>
Features
- Execute CMD commands through MCP
- TypeScript implementation
- Built on the official MCP SDK
- Cross-platform compatibility
Installation
Installing via Smithery
To install CMD Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install server-cmd --client claude
Manual Installation
npm install server-cmd
Prerequisites
- Node.js (v16 or higher recommended)
- npm or yarn package manager
Usage
import { MCPCmdServer } from 'server-cmd';
// Initialize the server
const server = new MCPCmdServer();
// Start the server
server.start();
Configuration
The server can be configured through environment variables or a configuration object:
const config = {
// Add your configuration options here
};
const server = new MCPCmdServer(config);
Development
To set up the development environment:
- Clone the repository:
git clone https://github.com/PhialsBasement/CMD-MCP-Server.git
cd CMD-MCP-Server
- Install dependencies:
npm install
- Build the project:
npm run build
Scripts
npm run build- Compile TypeScript to JavaScriptnpm run prepare- Prepare the package for publishing
Dependencies
@modelcontextprotocol/sdk: ^1.0.1glob: ^10.3.10zod-to-json-schema: ^3.23.5
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Security
Please note that executing command-line operations can be potentially dangerous. Make sure to implement proper security measures and input validation when using this server in production environments.
Support
For issues and feature requests, please use the GitHub issue tracker.
FAQ
- What is the CMD Executor MCP server?
- CMD Executor is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for CMD Executor?
- This profile displays 58 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★58 reviews- ★★★★★Evelyn Wang· Dec 28, 2024
Strong directory entry: CMD Executor surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Anaya Mensah· Dec 24, 2024
CMD Executor is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Aanya Jain· Dec 24, 2024
I recommend CMD Executor for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Amina Desai· Dec 8, 2024
CMD Executor has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Pratham Ware· Dec 4, 2024
CMD Executor reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Tariq Ndlovu· Nov 27, 2024
CMD Executor is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Sakshi Patil· Nov 23, 2024
I recommend CMD Executor for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Michael Tandon· Nov 19, 2024
Useful MCP listing: CMD Executor is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Amina Sharma· Nov 15, 2024
CMD Executor reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Fatima Srinivasan· Oct 18, 2024
We wired CMD Executor into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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