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Amazon Product Research MCP Server

Amazon Product Research MCP Server

by ludodelot

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.

Related MCP server: Amazon Product Intelligence Agent

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.

License

MIT © Ludovic Delot Bravo

Available Tools

2 tools
get_productC

Get detailed information about an Amazon product.

Inputs: product_id (required).

search_productsB

Search Amazon products by keyword.

Inputs: query (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.3/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools are clearly distinct: search_products finds products by keyword, while get_product retrieves detailed information for a specific product. No overlap or ambiguity exists between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern using snake_case (search_products, get_product), making the naming predictable and easily understandable.

    Tool Count3/5

    With only 2 tools, the set feels thin for a product research server. While it covers the basic search-and-detail flow, it lacks breadth seen in more comprehensive servers, but it is not extreme enough to be a 1 or 2.

    Completeness3/5

    The tool surface provides the minimum necessary for product research—searching and retrieving details—but notably lacks capabilities like browsing categories, accessing reviews, or comparing products, which are expected in a full research context.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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