Enables AI agents and LLMs to perform comprehensive file system operations including CRUD, search, archive, hashing, and duplicate detection via the Model Context Protocol.
Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.
Provides AI assistants with persistent memory through local ChromaDB vector storage, featuring automated file ingestion and batch processing for over 70 file types. It enables advanced vector search, EXIF metadata extraction for photos, and duplicate file detection across local directories.
Enables AI assistants to compare files and identify near-identical version families using deterministic evidence, so users can determine which drafts are current and which are safe to recycle without any file modifications.
Enables LLM agents to safely reclaim disk space by deleting build artifact directories like node_modules, .venv, and target, with strong guardrails to prevent accidental or malicious deletion.