Amazon Product Research MCP Server

A Model Context Protocol (MCP) server that gives an AI assistant (e.g. Claude Code) tools to search and inspect Amazon product data, over stdio.

Features

search_products — search products by keyword.
get_product — fetch full details for a single product by ID.
Written in strict TypeScript, validated at runtime with Zod.
Unit tested with Vitest.
Linted with ESLint (typescript-eslint) and formatted with Prettier.

Project structure

src/
├── index.ts              # Entry point: wires the server to a stdio transport
├── server.ts              # Registers MCP tools on the McpServer instance
├── types/
│   └── product.ts         # Shared Product type
└── tools/
    ├── product-data.ts     # In-memory product catalog (mock data)
    ├── search-products.ts  # search_products tool: input schema + handler
    └── get-product.ts      # get_product tool: input schema + handler
tests/
├── search-products.test.ts
└── get-product.test.ts

Requirements

Node.js 20+
npm

Getting started

npm install
npm run dev

This starts the server over stdio using tsx, ready to be connected to by an MCP client.

Connecting from Claude Code

claude mcp add amazon-research -- npx tsx /absolute/path/to/amazon-product-research-mcp/src/index.ts

Scripts

Command	Description
`npm run dev`	Run the server directly from TypeScript source.
`npm run build`	Type-check and compile to `dist/`.
`npm start`	Run the compiled server from `dist/`.
`npm test`	Run the unit test suite (Vitest).
`npm run lint`	Lint the codebase with ESLint.
`npm run format`	Format the codebase with Prettier.
`npm run format:check`	Check formatting without writing changes.

Tools reference

`search_products`

Search Amazon products by keyword (matches against the product name, case-insensitive).

Input

{ "query": "kindle" }

Output

[
  {
    "id": "kindle-paperwhite",
    "name": "Kindle Paperwhite",
    "price": 169.99,
    "currency": "USD",
    "rating": 4.7,
    "reviewCount": 12543,
    "description": "A high-resolution e-reader designed for reading comfortably indoors and outdoors."
  }
]

`get_product`

Get full details for a single product by its ID.

Input

{ "product_id": "kindle-paperwhite" }

Output: a single Product object, or null if no product matches.

Data

Product data currently lives in a small in-memory mock catalog (src/tools/product-data.ts) rather than a live Amazon API — this keeps the project self-contained and safe to run without any credentials. .env.example documents the environment variables a real API integration would need.