"Ray" matching MCP servers:

Enables local, provenance-aware literature search and retrieval for X-ray binary research, with tools for querying papers, fetching paper details, and accessing source information.

Enables AI assistants to search and read the full Ray Peat corpus and WikiPeatia wiki, including articles, books, interviews, newsletters, and forum posts, with full-text, semantic, and LLM-powered Q&A tools, plus access to Ray Peat's original articles.

Enables external agents to retrieve knowledge with source context through MCP tools for querying, listing collections, and obtaining document summaries.

A modular RAG service framework that exposes tools like query_knowledge_hub, list_collections, and get_document_summary via MCP protocol, enabling AI assistants to perform retrieval-augmented generation.

A pluggable, observable modular RAG framework that exposes query knowledge hub, list collections, and get document summary tools via MCP, enabling AI assistants to perform hybrid search and document retrieval with reranking.

Enables AI-powered dental X-ray analysis and treatment planning using YOLOv11 and clinical guideline RAG, integrated with MCP for use with Claude and other AI assistants.

Local-first memory for AI agents: one store shared by Claude Code, Codex CLI, Cursor, Pi, Hermes, OpenClaw, and any MCP client. Plain markdown with YAML frontmatter on your disk, hybrid BM25 + vector recall with per-result provenance (Recall X-ray), a correction contract, and the MemCorrect benchmark.

A pluggable, observable modular RAG framework exposing tools via MCP protocol for AI assistants like Copilot/Claude to query knowledge bases, list collections, and retrieve document summaries.

Enables AI assistants to perform retrieval-augmented generation through MCP tools for querying knowledge hubs, listing collections, and retrieving document summaries, with pluggable ingestion, hybrid search, and evaluation components.

A smart proxy that aggregates multiple downstream MCP servers and enables natural language search for tools, allowing clients like Claude Desktop to discover and use tools through semantic queries.

An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.

A production-minded RAG service for MCP that answers questions over your documents with hybrid retrieval, PII redaction, and source citations, packaged for Docker/Kubernetes.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

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.

Enables hybrid vector and keyword search over Azure AI Search indexes via an MCP tool, supporting query with embedding generation.

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).

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.

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 with LM Studio to provide a search_notes tool, allowing the chat model to retrieve and answer from a local Obsidian vault.

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.