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 MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.
A local-first MCP server that provides AI agents with safe codebase access through file discovery, hybrid lexical-semantic search, and project introspection. It features durable local memory and semantic indexing while keeping all data and processing entirely on your local machine.
A secure, Dockerized MCP server enabling AI assistants to perform file and directory CRUD operations like read, write, edit, search, and manage local files via natural language.
A privacy-first MCP server that provides local LLM-enhanced tools for code analysis, security scanning, and automated task execution using backends like Ollama and LM Studio. It enables symbol-aware code reviews and workspace exploration while ensuring that all code and analysis remain strictly on your local machine.
A local AI-powered file reader that connects a Python MCP server with Ollama's Mistral model for offline file summarization. It provides secure file discovery and reading capabilities without requiring API keys or cloud services.