"Amazon Web Services (AWS) information and resources" matching MCP servers:

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

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.

A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with your AWS environment. This allows for natural language querying and management of your AWS resources during conversations. Think of better Amazon Q alternative.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

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

Enables interaction with Adobe Commerce Catalog Services to retrieve product variants, price overrides, category permissions, and environment details via MCP.

Fetch live Amazon product data using Amazon Scraper API MCP server

Run SQL queries with AWS Athena to access data available from AWS Glue catalog.

Enables comprehensive search and browsing of Berlin city services. Also supports PDF form discovery, analysis, and filling with resilient caching.

Enables users to search for products, retrieve details, and manage their shopping cart on Amazon through the MCP framework. It also supports viewing order history and provides a demonstration of ordering capabilities within AI interfaces.

Enables AI agents to search and retrieve Israel's social services data, including service details, taxonomy, and location-based queries.

Enables interaction with Amazon's Product Advertising API to search for and retrieve product information from Amazon marketplaces. Supports multiple Amazon regions and marketplaces with configurable host, region, and partner credentials.

Lets Claude search Amazon products via multiple keyword queries and present curated results in an interactive carousel widget with add-to-cart functionality.

Provides Amazon search volume trends and growth signals to measure real consumer purchase intent, queryable by AI assistants.

Enables scraping Amazon product details and searching for products on Amazon through natural language queries. No API keys required as it scrapes publicly available Amazon pages.

A Multi-Agent Conversation Protocol Server that provides access to Google's Local Services API, enabling interaction with local service businesses information through natural language commands.

Enables searching Amazon India products, retrieving details, tracking prices, managing favorites, and more with fast caching.

Enables searching and reading AWS knowledge from sources the official AWS Knowledge MCP Server does not index, including re:Post community Q&A, kiro.dev documentation, and AWS Builder Center posts.

Enables web searches through DuckDuckGo without an API key and extracts readable main content from web pages.

MCP server for amazon.in — cheapest in-stock, best-value picks, and price history links.

Enables access to AWS documentation through natural language by fetching and converting documentation pages to markdown, searching AWS docs, and getting content recommendations for AWS service documentation.

Enables web search and web fetch operations using Ollama's hosted APIs, allowing MCP clients to search the web and retrieve page content.

Odysseus Web MCP is a standalone Model Context Protocol (MCP) server for safe public-web search and URL fetching.

MCP server for web page fetching (converting to Markdown/text with automatic fallback between Tavily and Firecrawl) and web search via Tavily.

A Model Context Protocol (MCP) server that enables searching AWS Black Belt Online Seminars and retrieving their transcripts.

Enables AI agents to search and fetch high-quality information from multiple sources, including general web APIs, Wikipedia, arXiv, Hacker News, Stack Exchange, and Crossref, with optional pro-mode deep research and clean markdown page extraction.

Enables a locally-run LLM to search the web, fetch pages as markdown, make arbitrary HTTP requests, and optionally render pages with headless Chromium.

Gives AI agents local web search and page reading with no API keys, layering a SearXNG-backed search cache with browser-based fallbacks and returning clean page text from HTML, PDF, JSON, and archived snapshots. Fetches run in Docker alongside the search engine with SSRF protection, egress filtering, and untrusted-content marking so agents can safely retrieve live web data.

Enables MCP-capable agents to perform local web research under a declared plan with session budgets, user-approved limit extensions, and guardrails for safe searching, page fetching, content extraction, and audit logging.

Enables agents to perform compact, cited web research within caller-set token caps, returning direct answers, short verbatim quotes, numbered sources, and noted gaps.