This article details how to build a 100% local MCP (Model Context Protocol) client using LlamaIndex, Ollama, and LightningAI. It provides a code walkthrough and explanation of the process, including setting up an SQLite MCP server and a locally served LLM.
An extensible Model Context Protocol (MCP) server that provides intelligent semantic code search for AI assistants. Built with local AI models using Matryoshka Representation Learning (MRL) for flexible embedding dimensions.
LLMII uses a local LLM to label metadata and index images. It does not rely on a cloud service or database. A visual language model runs on your computer and is used to create captions and keywords for images in a directory tree. The generated information is then added to each image file's metadata.
A personal productivity assistant that utilizes Retrieval-Augmented Generation (RAG). Allows users to chat with their documents and apps using various AI models. A local and private alternative to OpenAI GPTs and ChatGPT.
Saturday nights
