RAGAI Book Backend

Example Use Cases

• 1

  Semantic search capabilities over custom document embeddings.

• 2

  Secure, authenticated access to a RAG pipeline backend.

• 3

  Integration with OpenAI agents via the Model Context Protocol.

Description

This backend enables ingestion, chunking, embedding, and semantic search of documents using OpenAI and Qdrant, exposing these capabilities via the Model Context Protocol (MCP). It supports secure JWT authentication and is designed for integration with agentic systems like Claude Desktop. The server facilitates efficient retrieval-augmented generation pipelines for enhanced AI agent functionality.