Best RAG Tools Top 20

Firecrawl is the Web Data API for AI, turning web pages into clean, structured, LLM-friendly data with crawl, scrape, and search capabilities.

100+ AI Agent and RAG apps you can actually run — clone, customize, and ship. A great reference for quickly building LLM-powered applications.

A leading open-source RAG engine that fuses cutting-edge retrieval-augmented generation with agent capabilities to create a superior context layer for LLMs.

A high-throughput and memory-efficient inference and serving engine for LLMs, featuring PagedAttention, continuous batching, and optimized KV cache management for production deployments.

Comprehensive guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG applications.

Transforms complex documents like PDFs into LLM-ready markdown/JSON for Agentic workflows, supporting layout analysis, formula recognition, and table extraction.

Ready-to-run cloud templates for RAG, AI pipelines and enterprise search with live data, always in sync with Sharepoint, Google Drive, S3, Kafka and more.

Docling is an open-source document processing tool by IBM that converts PDF, Word, PPT, HTML and more into structured data for AI, purpose-built for GenAI and RAG pipelines.

AI-driven public opinion and trend monitor with multi-platform aggregation, RSS subscriptions, smart keyword filtering, AI-powered news analysis and briefings, supporting MCP integration and push notifications via WeChat, Feishu, DingTalk, Telegram and more.

Embedchain is a universal memory layer for AI agents, enabling quick integration of diverse data sources into LLMs for context-aware AI applications.

Mem0 is a long-term memory layer for AI agents, supporting cross-session memory management and personalized context retrieval.

Context7 is Upstash's context-engineering toolkit for agents, helping applications manage long context windows, retrieval injection, and history compression.

LlamaIndex is a data framework that provides the data connection layer for LLM applications, with strong RAG capabilities across diverse data sources and vector databases.

A comprehensive tutorial on AI agent principles and practice, systematically covering core concepts, framework usage and hands-on projects.

Open-source AI engine to run any model — LLMs, vision, voice, image, video — on any hardware without GPU. Provides OpenAI-compatible API for fully local, privacy-first AI inference.

Milvus is a high-performance open-source vector database built for AI applications. It supports storage, indexing, and similarity search of large-scale vector data, ideal for RAG, recommendation systems, and more.

Opinionated RAG framework for integrating GenAI into your apps. Works with any LLM, any vectorstore, any files — so you can focus on your product instead of building RAG pipelines.

A local knowledge base RAG and Agent application platform built on Langchain with support for ChatGLM, Qwen, Llama and other LLMs, offering conversation, knowledge base management, and agent capabilities.

A Python library by Google for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization, designed for data annotation and knowledge extraction workflows.