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

MCP server for AWS S3 — list buckets, browse objects, upload/download files, and generate presigned URLs.

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

Enables AI assistants to explore and manage S3-compatible object storage (AWS S3, RustFS, MinIO, Cloudflare R2) by listing buckets and objects, inspecting metadata, and reading object contents with capped range requests. Write operations such as upload and delete are available but disabled unless explicitly enabled, with optional bucket allow-listing and custom TLS trust.

An Amazon S3 Model Context Protocol server that allows Large Language Models like Claude to interact with AWS S3 storage, providing tools for listing buckets, listing objects, and retrieving object contents.

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.

A local-only codebase indexer that extracts syntax-aware chunks, creates embeddings locally, and enables semantic code search and symbol lookup via MCP.

This server enables interaction with Amazon S3 buckets for listing and retrieving objects, with efficient streaming for large files like PDFs, through the Model Context Protocol.

Enables file uploads to AWS S3 buckets with automatic MIME type detection.

Enables SQL database interaction with true server-side result paging, runtime-managed connection profiles, and SSH-bridged access for PostgreSQL.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables browsing S3 buckets and objects, and generating secure presigned URLs for downloads and uploads, through natural language commands in MCP clients like Claude Desktop.

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.

This server that distributes a single piece of content across 8+ channels (DEV.to, Hashnode, GitHub Discussions, Reddit, Bluesky, LinkedIn, Medium, Twitter) with automatic platform-specific adaptation, idempotent publishing, per-community anti-spam rules, and centralized state management.

MCP server exposing content contract validators (SEO.md, PRODUCTHUNT.md, LINKEDIN.md) as tools so AI agents can verify generated content against concrete rules without maintaining linters. It provides linting and JSON-LD export tools with config and content passed as parameters, not file paths.

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.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.

Provides AI agents with structured short-form content mechanics including hooks, script structures, retention strategies, and CTAs, along with auditing tools to avoid common posting failures.

Enables MCP clients to connect to AWS S3 buckets, list, upload, and read objects in various formats, supporting public and private buckets with multiple transport modes.

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

Read-only MySQL/MariaDB MCP server for running SELECT queries safely, with automatic read-only enforcement and query limits.