An intelligent Retrieval-Augmented Generation (RAG) application that uses the Model Context Protocol (MCP) to automatically decide between searching a private knowledge base or the web.
An MCP-based multi-agent retrieval-augmented generation system that enables question answering over academic papers with hybrid search, knowledge graph multi-hop reasoning, and source-cited answers.
A Model Context Protocol server that exposes a hybrid RAG pipeline (dense+sparse retrieval with reranking) for querying an enterprise knowledge base, enabling autonomous agents to search and retrieve relevant information.
A modular RAG framework exposing knowledge retrieval tools via MCP, enabling AI assistants to perform hybrid search, reranking, and multimodal document queries with full observability and evaluation.
A lightweight, domain-agnostic hybrid search engine for markdown corpora, exposed via the Model Context Protocol (MCP), optimized for serving SDK documentation to AI coding agents.