"Amazon DynamoDB" matching MCP servers:

An MCP server that gives LLM agents full access to Amazon DynamoDB, supporting table management, querying, scanning, and item CRUD operations.

Enables AI assistants to query Amazon search volume trends and growth signals for product research and consumer purchase intent analysis.

Live Amazon marketplace data for AI agents: product details, prices, reviews, keyword search, best-sellers, deals, offers and stock, and seller profiles across 20 marketplaces.

Remote MCP server with 19 e-commerce and IP-compliance data tools — Amazon product/review/search/niche/bestseller data, AI SERP & keyword trends, local Maps POI, WIPO trademark search, and PACER patent litigation. No scraping code or proxies needed; one API key unlocks all tools.

Gives Amazon Quick Desktop real shell access outside its sandbox, running commands as your own user with login-shell environment, synchronous execution, background jobs, process-tree cleanup on timeout, and an audit log. A narrow pattern-based guard blocks a handful of destructive commands while ordinary work — including targeted recursive deletes — passes through.

Enables AI agents to deploy and manage simulated AWS resources (like EC2, S3, DynamoDB) on a local Floci instance through natural language.

Enables intelligent navigation and extraction of documentation from websites, allowing Amazon Q to automatically discover relevant pages, extract clean content, and retrieve code examples from web documentation.

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.

Agent-native Amazon review intelligence — fetches verified reviews from 10 marketplaces via real Shulex OpenAPI (not scrapers) and produces copy-ready listing improvements grounded in actual customer language. Backed by a 2B-review historical dataset that Helium 10 / Jungle Scout can't replicate. Works in any MCP client (Claude Code, Claude Desktop, ChatGPT, Cursor, Windsurf, VS Code, Cline).

A local MCP server that enables querying Amazon Selling Partner API for profitability analysis (revenue, fees, COGS, net margin) and inventory alerts (FBA stock levels and low-stock warnings) using read-only operations.

Connects Claude to your Amazon Seller Central account via the Selling Partner API, enabling queries for recent orders, sales summaries, FBA inventory, and financial events.

Enables beginner Amazon India sellers to research product opportunities, estimate demand, analyze competition, calculate profitability, find suppliers, mine reviews, research keywords, and generate listings through Claude Desktop.

Hosted Amazon market-intelligence MCP for Claude and ChatGPT: query brands, sellers, ASINs, under-competed niches, the cross-seller operator network, observed buy-box history, and Amazon/Walmart cross-marketplace overlap. 65 read-only research tools over a pre-collected research dataset.

Enables AI applications to interact with Amazon Advertising API through the Model Context Protocol. Supports campaign management, performance reporting, audience targeting, and comprehensive advertising operations across Amazon's advertising ecosystem.

A Model Context Protocol server implementation that enables Claude to perform AWS operations on S3 and DynamoDB services through natural language commands.

Enables access to Amazon Managed Prometheus workspaces through natural language queries. Supports listing workspaces, executing PromQL queries, and retrieving workspace details and metrics with AWS authentication.

Enables Claude to read and search an Amazon Ads account, pull suggested bids and reports, and propose changes as approved plans with rollback support.

Enables workout logging, volume calculation, exercise database search with 1500+ exercises, and AI-powered workout plan generation with DynamoDB persistence.

A high-performance Model Context Protocol (MCP) server that provides seamless integration with Amazon DataZone services. This server enables AI assistants and applications to interact with Amazon DataZone APIs through a standardized interface.

Enables querying Amazon Neptune databases and analytics graphs using openCypher or Gremlin. It provides tools for executing queries, retrieving graph schemas, and monitoring connection status.