Rag Packages

RAG (Retrieval-Augmented Generation) library for NestJS with vector database integration

A NodeJS RAG framework to easily work with LLMs and custom datasets

Client SDK for Memobase

Markdown Content Preprocessor - Fetch web pages, extract content, convert to clean Markdown

A Model Context Protocol server for searching Svelte 5 documentation using OpenAI's Retrieval API

> [!warning] > This package is still in **beta** and is subject to breaking changes. Use it with caution.

A Model Context Protocol server for Prem AI - enables AI assistants to interact with Prem's ecosystem for chat completions and RAG capabilities.

Model Context Protocol (MCP) server for seamless integration with Onyx AI knowledge bases

An MCP Server for RAG Web Browser Actor

A Model Context Protocol server for fetching and storing documentation in a vector database, enabling semantic search and retrieval to augment LLM capabilities with relevant documentation context.

[](https://smithery.ai/server/@pbteja1998/sourcesyncai-mcp)

MCP server providing RAG capabilities for SCOM framework code generation

Node.js client for Chunkr API

An MCP server for semantic documentation search and retrieval using vector databases to augment LLM capabilities.

SDK for interacting with RagFlow API

A Model Context Protocol server for fetching and storing documentation in a vector database, enabling semantic search and retrieval to augment LLM capabilities with relevant documentation context.

The Retrieval-Augmented Generation (RAG) module contains document processing and embedding utilities.

The core foundation of the Mastra framework, providing essential components and interfaces for building AI-powered applications.

RagRabbit React SDK

ReAI RAG,向量数据库，EMBEDDING，图谱