CLI Exec▌
by jakenuts
CLI Exec offers a powerful CLI interface for command line execution, with timeout, ANSI code stripping, and error handli
Provides powerful CLI command execution capabilities, enabling structured output for shell commands with features like timeout handling, ANSI code stripping, and error management for system administration and DevOps workflows.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / System administrators automating server tasks
- / DevOps engineers building deployment workflows
- / Developers running build scripts and tests
- / Infrastructure automation and monitoring
capabilities
- / Execute shell commands with timeout handling
- / Run multiple commands in sequence within a working directory
- / Strip ANSI codes from command output
- / Return structured results with exit codes and execution duration
- / Handle command errors gracefully
- / Stop execution on first command failure
what it does
Executes shell commands with structured output including exit codes, stdout/stderr, and error handling. Provides both raw command execution and multi-command workflows in specific directories.
about
CLI Exec is a community-built MCP server published by jakenuts that provides AI assistants with tools and capabilities via the Model Context Protocol. CLI Exec offers a powerful CLI interface for command line execution, with timeout, ANSI code stripping, and error handli It is categorized under developer tools. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install CLI Exec 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
CLI Exec is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
mcp-cli-exec MCP Server
A powerful CLI command execution MCP server that enables running shell commands with structured output. This package focuses specifically on command execution functionality, differentiating it from other MCP CLI tools.
Features
Tools
cli-exec-raw
Execute a raw CLI command and return structured output
- Takes a command string and optional timeout (default: 5 minutes)
- Returns detailed execution results including stdout, stderr, exit code
- Handles errors gracefully with structured error responses
cli-exec
Execute one or more CLI commands in a specific working directory
- Supports single commands, && chained commands, or array of commands
- All commands execute in the specified working directory
- Returns detailed results for each command:
- Success/failure status
- Exit code
- stdout and stderr (ANSI codes stripped)
- Execution duration
- Working directory
- Stops on first command failure
- Optional timeout per command (default: 5 minutes)
Note: Due to execution context limitations, each command runs independently. Directory changes (cd) within commands do not affect subsequent commands. All commands execute in the initially specified working directory.
Output Format
Commands return structured results including:
- Success/failure status
- Exit code
- stdout and stderr (with ANSI codes stripped)
- Execution duration
- Working directory
- Detailed error information if applicable
Example Usage
cli-exec-raw
Simple command execution:
{
"command": "echo Hello World"
}
With timeout:
{
"command": "long-running-script.sh",
"timeout": 300000
}
cli-exec
Single command in specific directory:
{
"workingDirectory": "/path/to/project",
"commands": "npm install"
}
Multiple commands (all run in the same working directory):
{
"workingDirectory": "C:\project",
"commands": [
"dir /b",
"npm run build"
]
}
Installation
Optionally install from npm:
npm install -g mcp-cli-exec
# or with pnpm
pnpm add -g mcp-cli-exec
Or just use npx in your configuration
For Cline VSCode Extension
Add to %APPDATA%/Code - Insiders/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json:
{
"mcpServers": {
"mcp-cli-exec": {
"command": "npx",
"args": ["-y", "mcp-cli-exec"]
}
}
}
For Claude Desktop
Add to the appropriate config file:
Windows: %APPDATA%/Claude/claude_desktop_config.json
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"mcp-cli-exec": {
"command": "npx",
"args": ["-y", "mcp-cli-exec"]
}
}
}
Special Windows Configuration
If you encounter the ENOENT spawn npx issue on Windows, use this alternative configuration that specifies the full paths:
{
"mcpServers": {
"mcp-cli-exec": {
"command": "C:\Users\jim\AppData\Roaming\
vm\v22.1.0\
ode.exe",
"args": [
"C:\Users\jim\AppData\Roaming\
pm\
ode_modules\
pm\bin\
px-cli.js",
"-y",
"mcp-cli-exec"
]
}
}
}
Development
Install dependencies:
pnpm install
Build the server:
pnpm run build
For development with auto-rebuild:
pnpm run watch
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. The MCP Inspector provides helpful debugging tools:
pnpm run inspector
This will provide a URL to access the inspector in your browser, where you can:
- View all MCP messages
- Inspect request/response payloads
- Test tools interactively
- Monitor server state
Error Handling
The server includes comprehensive error handling:
- Input validation for all tool parameters
- Structured error responses
- Command timeout handling
- Working directory validation
- ANSI code stripping for clean output
Technical Details
- Built with TypeScript and the MCP SDK
- Uses execa for reliable command execution
- Default command timeout: 5 minutes
- Supports Windows and Unix-like systems (use appropriate commands for your OS, e.g., 'dir' vs 'ls')
- Executes commands sequentially, stopping on first failure
- Each command runs independently in the specified working directory
FAQ
- What is the CLI Exec MCP server?
- CLI Exec 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 CLI Exec?
- This profile displays 64 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 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
4.7★★★★★64 reviews- ★★★★★Camila Smith· Dec 24, 2024
CLI Exec has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Anaya Martin· Dec 20, 2024
We evaluated CLI Exec against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Evelyn Perez· Dec 16, 2024
CLI Exec has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Anika Okafor· Dec 12, 2024
CLI Exec reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Dec 8, 2024
We evaluated CLI Exec against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Rahul Santra· Nov 27, 2024
Useful MCP listing: CLI Exec is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Amina Khanna· Nov 15, 2024
CLI Exec is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Anika Mensah· Nov 11, 2024
Useful MCP listing: CLI Exec is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Yuki Liu· Nov 7, 2024
Strong directory entry: CLI Exec surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Yuki Yang· Nov 7, 2024
CLI Exec is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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