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Give MCP agents direct local access to files, Python, Node.js, and shell.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "shell-0" yet — see the docs or source repo.
Please access the local log directory, count error logs from the last 24 hours, and output a time-sorted summary.
Returns log statistics and a cleaned, organized error summary.
Please run common system diagnostic commands to check disk usage and current process resource consumption, then give a brief conclusion.
Returns command outputs and summarizes disk and process resource status.
Please read a local CSV file, use Python to calculate missing values and basic distributions for each column, and output the analysis.
Returns a dataset overview, missing-value statistics, and basic analysis results.
Developers can let an MCP agent access the local filesystem and run Python, Node.js, or shell commands for code and scripting tasks. It fits workflows that need direct execution on the local machine.
Ops users can use this tool to run local commands and inspect files or system state to help diagnose environment issues. Its key characteristic is unsandboxed access to the local machine.
Data analysts can have the agent read local data files and perform basic processing or analysis through Python or Node.js. This is useful when data is stored locally and needs direct computation.
It is an MCP tool that gives agents direct access to the local machine, including the filesystem, Python, Node.js, and shell commands. The description explicitly says this access is unsandboxed.
Based on the provided information, it at least involves a local machine environment and access to the filesystem, Python, Node.js, and shell commands. For exact dependencies and setup, see the source repository.
The description emphasizes unsandboxed local access rather than execution in a restricted environment. That means the agent can interact with local machine resources more directly.
Execute shell commands for automation, DevOps tasks, and developer workflows.
Give AI coding assistants direct local shell access for bash-driven development.
Execute shell commands securely over MCP for controlled dev and ops workflows.
Execute local shell commands and manage files from MCP clients.
Map shell commands into standard MCP tools with single-file YAML specs.
Securely equips AI agents with executable tools for commands, search, and file operations.