"Exploring RAG through defined workspaces" matching MCP servers:

Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.

Minimal RAG-over-a-corpus MCP retrieval: search_knowledge returns cited chunks. Local embeddings.

RAG Vault lets your AI coding assistant search your private documents locally. Everything runs on your machine and your data stays private.

Enables coding agents to retrieve project context from an AnythingLLM RAG at session start and write back human-approved durable facts via five workflow-shaped tools.

MCP bridge to a multimodal RAG service, enabling hybrid search and Q&A over documents with tools for knowledge base queries and health checks.

Keyless local RAG over your own documents (ChromaDB) with traceable citations, exposed as MCP tools and a FastAPI endpoint.

A RAG-based knowledge base system supporting document processing, semantic search, and intelligent Q\&A with multiple AI model integrations.

Enables LLMs to perform conceptual search over local PDF/EPUB documents using a RAG pipeline with corpus-driven concept extraction and WordNet enrichment.

A modular RAG server with hybrid search and LLM rerank, exposing 3 MCP tools for AI clients like Claude Desktop and Cursor.

Enables agents to retrieve relevant context from local documents via MCP tools, supporting ingestion, semantic search, metadata filtering, and evidence inspection entirely on-device.

Local MCP server that provides a search_documents tool to query a RAG pipeline built with Ollama embeddings and ChromaDB, enabling Claude Desktop to retrieve relevant document chunks.

Hybrid RAG over Claude Code and Hermes session history via MCP tools for search, ingest, and context injection.

MCP server that enables semantic search over PDF documents using RAG with ChromaDB and OpenAI embeddings.

A CLI tool and MCP server that turns markdown documentation into a searchable, queryable knowledge base.

MCP server for Fathom Works RAG that exposes a self-hosted knowledge base as tools for any MCP-capable LLM to query documents, manage libraries, and ingest files or URLs.

Implements Retrieval-Augmented Generation (RAG) using GroundX and OpenAI, allowing users to ingest documents and perform semantic searches with advanced context handling through Modern Context Processing (MCP).

Connects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).

Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.

MCP server that integrates Apache Ranger authorization with RAG, enforcing Ranger policies to control access to knowledge bases before forwarding queries to RAG Studio.

Enables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.