"Notes or documentation related to 'rag'" matching MCP servers:

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

Enables indexing and retrieving notes with full-text search using SQLite, plus building knowledge graphs to find relationships between concepts. Supports natural language note management, tagging, and semantic connections.

A privacy-preserving local RAG system integrated with MCP, enabling natural language queries over ingested documents and a SQLite database through vector search and local database tools.

Connects to a PostgreSQL database (pgvector) to perform semantic retrieval via the search_documents tool, returning raw document snippets for LLM synthesis.

Read-only MCP server that exposes ZAP's RAG search modes (plain, hybrid, hybrid_rerank) for agents to perform semantic code retrieval.

Enables discovery of Fabric/Power BI workspaces and semantic models, execution of DAX queries, and generation of executive HTML reports with visualizations.

Transforms SAP S/4HANA or ECC systems into conversational AI interfaces by exposing all OData services as dynamic MCP tools. Enables natural language interactions with ERP data including querying, creating, updating, and deleting entities through SAP BTP integration.

Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.

Transforms SAP S/4HANA or ECC systems into conversational AI interfaces by exposing all OData services as dynamic MCP tools. Enables natural language interactions with ERP data for querying, creating, updating, and deleting business entities through SAP BTP integration.

MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.

A secure database query service built on FastMCP framework that allows users to query MySQL databases using natural language, with comprehensive permission management and security controls.

Enables semantic search and retrieval of code files using embeddings stored in PostgreSQL. Supports intelligent codebase exploration through natural language queries, file listing, and content retrieval.

MCP server enabling natural-language querying of SQLite databases via schema discovery, GraphRAG retrieval, and safely guarded read-only SQL execution.

A private MCP server that converts natural-language questions into embeddings and performs semantic retrieval over document chunks stored in BigQuery, returning structured passages with source and page metadata. It serves as the read-only retrieval layer for a document-grounded chatbot.

A Model Context Protocol server for reading TiDB RAG knowledge base, enabling browsing, searching, and vector search of knowledge entries.

Enables natural-language querying of a mock legacy healthcare database and returns validated FHIR resources (Patient, Observation, Condition).

AI-powered expense tracking MCP server that connects LLM clients to PostgreSQL for natural language expense management.

Exposes any SQLite database as read-only MCP tools for AI assistants, enabling listing tables, describing schemas, and running SELECT queries with filtering, ordering, and pagination.

Enables RAG (Retrieval-Augmented Generation) with tools for vector search, document access, and OpenAI integration, plus MySQL storage and file system operations via MCP.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.