"A platform for finding Amazon products based on various interests" matching MCP servers:

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

placement for the depractaed Amazon Product Advertising endpoint. You ask Claude to find something, it searches the live Amazon catalogue, and it hands you back a finished HTML card - image, price, savings, star rating, your Associates tag already baked into the link, and the disclosure footer Amazon requires, by Houtini

MCP server wrapping a mock internal ops platform (FastAPI + SQLite) so Claude Code can read and write employee, project, task, and time data through natural language.

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).

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.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

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.

An MCP server that enables AI assistants to interact with Amazon Connect contact centers, providing 88 tools, 91 configuration templates, and multi-region support.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

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 AI agents to interact with ServiceNow through MCP, providing schema inspection, record CRUD, attachments, audit, Flow Designer, and platform investigations with policy-guarded access.

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.

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.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

MCP server for grounded analysis of synthetic electric-taxi operations data, exposing tools for aggregated metrics, charging risk, and policy retrieval.

MCP server that exposes the Amazon Selling Partner API to Claude Desktop and any other MCP client. It wraps the python-amazon-sp-api SDK and ships 55+ tools across 19 SP-API scopes with automatic pagination, throttle-aware retry and multi-marketplace support.

About MCP server for Google Agent Platform Docs — Google AI + Vertex AI. 3400+ pages searchable by AI agents.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.