"An MCP server for indexing S3 content into a RAG vector database" matching MCP servers:

Enables integrating RAG into AI agents via MCP server, supporting multiple vector database technologies.

A production-grade MCP server for integrating RAG into AI agents, supporting multiple vector databases with enterprise security and dynamic tool selection.

Integrates RAG into AI agents via MCP Server, supporting multiple vector database technologies for collection management and search operations.

A read-only MCP server that enables AI agents to explore database schemas and execute safe queries on PostgreSQL and MySQL.

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.

An MCP server that enables interacting with Google's Indexing API, allowing agents to submit URLs to Google for indexing or removal from search results through natural language commands.

A shared, persistent MCP memory server for coding agents that enables storing and retrieving project decisions and context across different tools like Claude Code, Codex, and Cursor using semantic vector search.

Extract content from URLs, documents, videos, and audio files using intelligent auto-engine selection. Supports web pages, PDFs, Word docs, YouTube transcripts, and more with structured JSON responses.

A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

A Model Context Protocol server that enables LLMs like Claude to interact with SQLite and SQL Server databases, allowing for schema inspection and SQL query execution.

Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.

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.

Turns your Readwise library into a blazing-fast semantic search engine with a streaming MCP server for LLM clients, supporting vector search, nightly syncs, and deployment on serverless platforms like Vercel.

Enables agents to interact with any S3-compatible storage (AWS S3, LocalStack, MinIO) via MCP, providing tools like list, read, write, delete objects and buckets.

Enables AI agents to query S3 data lakes using natural language, with support for CSV, JSON, Parquet and tools for data discovery, analysis, and metadata exploration.

An extensible MCP server for database operations that supports PostgreSQL for managing schemas, tables, data, and user permissions. It features automatic migration recording for DDL changes and integrates with various AI-powered editors like Cursor, Zed, and Claude Code.

A modular MCP server that enables interaction with multiple database types including PostgreSQL, MySQL, SQLite, Redis, MongoDB, and LDAP. It provides tools for executing queries, managing SQL commands, and exploring database schemas with configurable read-only security.

A specialized Model Context Protocol server that enhances AI-assisted medical learning by connecting Claude Desktop to PubMed, NCBI Bookshelf, and user documents for searching, retrieving, and analyzing medical education content.

Provides a natural language interface for querying and managing PostgreSQL, MySQL, MariaDB, MSSQL, and SQLite databases using the Model Context Protocol. Users can explore database schemas and visualize query results through an integrated web dashboard.