MCP server that enables AI to read, search, and edit local files securely without external data exposure, using local LLMs via Ollama and integrating with Open WebUI or Claude Desktop.
A local MCP server that gives Ollama language models sandboxed file management tools—read, write, list, and recoverable delete—within configurable workspace directories, keeping everything local and secure.
A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.
A Python MCP server that exposes local Ollama models as tools for AI assistants, enabling chat, generation, embeddings, and model management without cloud APIs.
Zero-config MCP server that connects local codebases to AI assistants, providing secure project tree, regex search, file reading, and tech stack tools locally.
A beginner MCP server that enables Claude to read local text, CSV, and Markdown files. Built as a learning project to understand how to connect AI to local file systems using the MCP protocol.