"Amazon RDS" matching MCP servers:

Enables management of Amazon Bedrock Knowledge Bases including creation, data source configuration, document ingestion, and RAG (Retrieval-Augmented Generation) queries with support for multiple embedding models and custom parsing/chunking strategies.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Persistent, local, cross-IDE memory for AI agents — markdown source of truth, LanceDB-powered semantic search, zero cloud dependency

Enables LLMs to run complex graph algorithms on Neo4j databases, answering graph-related questions by selecting and executing appropriate parameterised graph algorithms.

The Model Context Protocol (MCP) server provides a conversational interface for the exploration and analysis of RDF Turtle Knowledge Graph in Local File mode or SPARQL Endpoint.

Enables comprehensive management of Google Ads accounts by allowing users to create campaigns, manage keywords, and generate performance reports through a context-aware interface. It features a three-layer architecture that integrates product knowledge and historical campaign data to support intelligent decision-making.

Serverless document and media processing with AI chat. Upload documents, images, video, and audio — extract text with OCR or transcription — query using Amazon Bedrock.

An MCP server that exposes an append-only, SQLite-backed event log for parallel research agents, providing append_delta, pull_deltas, and list_tasks tools over stdio.

A searchable long-term memory server for AI agents using BM25 indexing over document chunks, enabling durable recall across sessions without cloud dependencies.

MCP servers for querying Brick and 223P ontologies, enabling abbreviation expansion, term/property lookup, and definition retrieval.

Persistent memory for AI agents — organized by time and space. Important memories get promoted, noise decays naturally, and related knowledge clusters into a browsable topic tree. Fully automatic.

Local-first MCP memory server providing persistent, versioned, queryable memory for AI agents using JSON categories and SQLite FTS5, with optional fleet sync.

MCP server for enabling data extraction and context retrieval for agents, storing information in a knowledge graph using Amazon Neptune or FalkorDB.

MCP server for Outline knowledge base implemented on Rust as one statically linked executable file for Linux/MacOS/Windows.

Enables intelligent RSS feed management with AI-powered semantic search, advanced filtering, and a comprehensive reading workflow. Supports OPML parsing, article organization with status tracking, and token-efficient browsing of large feed collections.

A local-first memory retrieval engine for coding agents that stores project and conversation memory and retrieves source-grounded context through MCP.