An MCP server that exposes filesystem operations — listing directories, reading, writing, and searching files — as tools an LLM can discover and invoke at runtime.
A lightweight, stdio-based MCP server enabling AI assistants to perform local file system operations like reading, writing, searching, and executing commands.
High-performance MCP server giving AI agents advanced filesystem and automation capabilities on Windows, with 26 tools across file I/O, search, Git, process management, and more.
A beginner-friendly MCP server that enables AI to explore file systems through tools for listing directories, reading files, searching with wildcards, and getting file metadata. Perfect for learning MCP development while providing practical file system interaction capabilities.
An MCP server that gives AI agents git repository access: status, log, diff, branch, commit, push, pull, tag, stash, remotes — 24 tools, zero dependencies, pure Python stdlib (subprocess).
A self-hosted MCP server that gives AI agents controlled access to a machine: filesystem, shell, background processes, git, web fetching and persistent key-value memory.