"Options for Amazon or AWS Data Integrations" matching MCP servers:

Enables modular retrieval-augmented generation with multiple data sources (documents, FAQ, status) and dynamic routing using Gemini or fallback.

Enables agents to retrieve indexed Amazon Ads, Seller Central, and Vendor Central knowledge by browsing tags, searching tools, inspecting schemas, and executing chained calls.

An MCP server that enables users to retrieve information from AWS Knowledge Bases using RAG (Retrieval-Augmented Generation) via Bedrock Agent Runtime.

This read-only MCP Server allows you to connect to Amazon Redshift data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

This read-only MCP Server allows you to connect to Amazon Marketplace data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

This read-only MCP Server allows you to connect to Amazon DynamoDB data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

A proof of concept MCP server for Apache OFBiz

This MCP server enables any MCP client to perform web searches over HTTP using just an endpoint URL and API key, abstracting away AWS SigV4 signing and Bedrock AgentCore protocol translation entirely server-side.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Enables natural language querying of PostgreSQL via MCP, combining SQL, vector search, and knowledge graph with automatic routing and token-aware curation.

Enables AI-powered Amazon product searches and recommendations by integrating the Amazon API with Hugging Face models. It allows users to filter products by price and specific features to receive tailored shopping suggestions.

Enables querying and analyzing user, product, and order data with filtering capabilities and real-time statistics. Supports WebSocket connections to XiaoZhi AI platform with automatic reconnection.

Automatically routes natural language questions to RAG or Text2SQL paths to answer queries about virtual construction site data, supporting semantic search and structured aggregation.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.