"Shelly" matching MCP servers:

A secure shell command execution server implementing the Model Context Protocol (MCP). This server allows remote execution of whitelisted shell commands with support for stdin input.

A bridge server that provides access to an Odoo shell environment, allowing execution of Python code within an Odoo database context for model introspection and database operations.

Provides direct, unsandboxed local machine access via filesystem, Python, Node.js, and shell commands for MCP agents.

Allows executing shell commands within a secure Docker container through Claude's MCP interface, providing Kubernetes tools and isolated environment without host Docker daemon access.

A secure MCP server for executing whitelisted shell commands with resource and timeout controls, designed for integration with Claude and other MCP-compatible LLMs.

A Node.js implementation of the Model Context Protocol that provides secure shell command execution capabilities, allowing AI models like Claude to run shell commands in a controlled environment with built-in security measures.

A secure server that implements the Model Context Protocol (MCP) to enable controlled execution of authorized shell commands with stdin support.

Provides a controlled escape hatch for director-mode AI agents to run shell commands, write and edit files, execute Python code, supervise detached background jobs, acquire locks, and capture screenshots.

Runs shell commands inside an existing microsandbox sandbox rather than on the Windows host, tracking the working directory and translating paths between the host project folder and the sandbox mount. Exposes tools for foreground or background execution with timeouts, output retrieval, killing processes, and listing them.

Enables executing local commands via an argv-based tool with optional non-interactive sudo, command allowlisting, and filesystem write confinement using Bubblewrap.

A Node.js MCP server that wraps the Claude Code CLI to enable parallel execution of AI requests for code generation, editing, and refactoring. It features built-in retry logic, model selection, and JSON validation for structured outputs.

Enables AI assistants to create isolated Kubernetes Pod sessions for real-time shell command execution, file management, and Node.js code execution, with automatic TTL-based cleanup.

Provides a stateful Django shell environment that allows AI assistants to execute Python code directly against Django projects. Maintains persistent session state between calls, enabling iterative exploration of models, queries, and debugging.

A secure interface that enables language models to execute shell commands on the host operating system through the Model Context Protocol.

Provides safe shell command execution capabilities for AI agents and tools like VS Code Copilot through a whitelist-based filtering system.