Generate a temporary working memory with a specified time-to-live, enabling AI systems to store and manage content and embeddings for short-term task continuity and context retention.
Create or update Python files directly within a working directory or system-wide. Specify file path, content, and overwrite option to manage Python scripts efficiently.
Set the current working directory for an SSH connection using the provided connection ID and directory path, enabling efficient navigation and operations on remote systems via SSH MCP Server.
The tool retrieves the current working directory path on the MCP server, enabling users to track their location during terminal operations or file system navigation.
Analyze detailed differences between a working directory and a specific Git commit. Provides file-by-file changes, insertion/deletion counts, change types, and optional diff content for precise version control tracking.
An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.
Enables AI models to perform file system operations (reading, creating, and listing files) on a local file system through a standardized Model Context Protocol interface.