RAG Knowledge Base
Provides a model context protocol server for retrieval-augmented generation queries against a text-based knowledge base.
Rag-mcp is an intricate retrieval-augmented generation (RAG) system operating as a Model Context Protocol (MCP) server, designed to provide advanced querying capabilities against a textual knowledge base. It leverages PostgreSQL with the pgvector extension to store and manage text embeddings, which are generated via an OpenAI-compatible API. The system exposes distinct search modalities, including semantic, question/answer, and style-based search, enabling AI agents and clients to perform nuanced information retrieval for RAG tasks. Its architecture is built for extensibility, allowing for the integration of custom search functionalities.
