---
title: "Agentset"
description: "An open-source RAG platform for building intelligent, document-based applications quickly and efficiently."
category: "mcp-servers"
tags: ["RAG", "AI applications", "document processing", "chatbots", "knowledge bases"]
tech_stack: ["Vector Databases", "Large Language Models (LLMs)", "Embedding Models", "Retrieval Pipelines"]
---

Agentset is an open-source platform designed for Retrieval-Augmented Generation (RAG). It helps developers build advanced applications that tap into external knowledge sources.

With Agentset, you get the tools you need to ingest, process, and retrieve information from documents. This information helps large language models (LLMs) provide responses that are more accurate and relevant to the context. By using this method, you can reduce inaccuracies and improve the trustworthiness of AI applications.

Agentset simplifies the tricky parts of working with vector databases, embedding models, and retrieval pipelines. This lets you quickly prototype and launch smart systems, like AI chatbots, research assistants, and enterprise knowledge bases.

Developers can concentrate on application logic and user experience, speeding up the process from idea to a fully functioning AI agent that understands documents. This platform is perfect for creating applications that need reliable interactions with specific types of text, such as technical manuals, legal documents, or internal company knowledge.