"Hybrid RAG System for Indexing DevOps eBooks and Online Documentation" matching MCP servers:

Enables AI agents to use a hybrid dense+sparse RAG system with tag-based long-term memory (importance, knowledge-type decay, access-frequency boost) via MCP tools for document ingestion, hybrid search, staged reranking, forgetting, and index management.

A local MCP server enabling hybrid search over documents, memory, and knowledge graphs for retrieval-augmented generation, with tools for SQLite, semantic memory, and entity-relationship queries.

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.

Unified MCP server with 46 tools for AI expert consultations, memory service integration (semantic search, knowledge graphs), workflow automation, and code sandboxing.

Universal FastMCP bridge into a hybrid memory stack, enabling MCP-capable agents to save, search, read, and recall memories using OpenViking and Honcho backends.

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.

Enables semantic search and question answering over a knowledge base using hybrid retrieval and grounded answers, all running offline with no API keys.

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.

Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.

Offline RAG MCP server that indexes documents into SQLite with hybrid vector and lexical search, and enables natural language queries via Claude.

Local-first knowledge system for reasoning agents, exposing facts, evidence, documents, retrieval, and audit history through a thin stdio MCP server.

Combines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.

Enables document-based Q&A with multi-modal RAG, hybrid retrieval, knowledge graph reasoning, and multi-agent orchestration via MCP tools.

Enables AI assistants to search and retrieve information from your knowledge base using RAG (Retrieval-Augmented Generation) with hybrid search, document indexing, and ChromaDB vector storage.

A headless local knowledge library and RAG substrate that enables LLM clients to search, retrieve chunks, and list documentation packs through read-only MCP tools.

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

Cross-project memory for Claude Code, enabling local semantic recall and secure, git-versioned markdown storage of reusable knowledge across repositories.

Enables persistent, searchable memory for Claude Code by storing session knowledge in a local PostgreSQL + pgvector database, with hybrid vector and full-text search, automatic session mining, and knowledge graph curation.

Hybrid RAG pipeline that indexes documents and exposes them via an MCP server, enabling natural language queries to retrieve relevant context chunks for LLMs.

Enables MCP clients to manage Wiki.js pages, users, and groups via CRUD tools and to perform semantic RAG search over wiki content with hybrid vector and lexical retrieval.