Amazon Product Advertising API
Integrate with the Amazon Product Advertising API to search for products and access product information.
Amazon PA-API MCP Service
A Model Context Protocol (MCP) service for Amazon Product Advertising API integration. This project uses the Python SDK officially provided at Product Advertising API 5.0.
Integration in Claude & Cursor
For configuring host, region and markeplace, consult the Locale Reference for Product Advertising API documentation.
{
"mcpServers": {
"amazon-paapi": {
"command": "uvx",
"args": [
"mcp-amazon-paapi"
],
"env": {
"PAAPI_ACCESS_KEY": "your-access-key",
"PAAPI_SECRET_KEY": "your-secret-key",
"PAAPI_PARTNER_TAG": "your-partner-tag",
"PAAPI_HOST": "webservices.amazon.de", // select EU or US servers and region
"PAAPI_REGION": "eu-west-1",
"PAAPI_MARKETPLACE": "www.amazon.de" // set your preferred marketplace
}
}
}
}
Project Structure
mcp-amazon-paapi/
├── src/
│ └── mcp_amazon_paapi/ # Main package
│ ├── __init__.py # Package initialization
│ ├── service.py # Amazon PA-API service class with dependency injection
│ ├── server.py # FastMCP server implementation
│ └── _vendor/ # Vendored dependencies
│ └── paapi5_python_sdk/ # Amazon PA-API Python SDK
├── test/ # Test suite
│ ├── __init__.py # Test package initialization
│ └── test_service.py # Tests for service module
├── pyproject.toml # Project configuration and dependencies
├── uv.lock # Dependency lock file
├── README.md # Project documentation
Local Setup
Initial Setup
# Sync dependencies from uv.lock (creates virtual environment automatically)
uv sync
# Alternatively, activate the virtual environment manually
source .venv/bin/activate # Linux/Mac
# or
.venv\Scripts\activate # Windows
Environment Variables
export PAAPI_ACCESS_KEY="your-access-key"
export PAAPI_SECRET_KEY="your-secret-key"
export PAAPI_PARTNER_TAG="your-partner-tag"
export PAAPI_HOST="webservices.amazon.de" # optional defaults to webservices.amazon.de
export PAAPI_REGION="eu-west-1" # optional defaults to eu-west-1
export PAAPI_MARKETPLACE="www.amazon.de" # optional, defaults to www.amazon.de
Testing
Run the simple test suite:
# Run all tests with uv (recommended)
uv run python -m pytest test/test_service.py -v
# Or if you have activated the virtual environment
pytest test/test_service.py -v
The test suite includes:
- Service initialization tests
- Configuration management tests
- Search functionality tests with mocking
- Error handling tests
Usage
from service import AmazonPAAPIService
# Create service (uses environment variables)
service = AmazonPAAPIService()
# Search for items
items = service.search_items("echo dot", "Electronics", 5)
Running the MCP Server
# Run directly with uv (recommended)
uv run python server.py
# Or if you have activated the virtual environment
python server.py
संबंधित सर्वर
Mapbox
Unlock geospatial intelligence through Mapbox APIs like geocoding, POI search, directions, isochrones and more.
Zenn Articles
A server for searching articles on the Zenn blogging platform.
BrowseAI Dev
Evidence-backed web research for AI agents. BM25+NLI claim verification, confidence scores, citations, contradiction detection. 12 MCP tools. Works with Claude Desktop, Cursor, Windsurf. Python SDK (pip install browseaidev), LangChain, CrewAI, LlamaIndex integrations. npx browseai-dev
domain-search-mcp
Domain Search MCP is an open-source MCP server that gives AI assistants the ability to check domain availability in real-time.
Rememberizer MCP Server for Common Knowledge
Access and search personal or team knowledge repositories, including documents and Slack discussions, using semantic search and retrieval tools.
EzBiz Business Intelligence
AI-powered competitive analysis, review monitoring, web presence scoring, and market research for businesses.
Agntic AI for Research Papers
Search and extract information about research papers from arXiv.
SearchAPI
Provides standardized access to Google Maps, Google Flights, Google Hotels, and other services via the SearchAPI.
Releasebot
Releasebot finds and watches release note sources from hundreds of products and companies.
NPMLens MCP
NPMLens MCP lets your coding agent (such as Claude, Cursor, Copilot, Gemini or Codex) search the npm registry and fetch package context (README, downloads, GitHub info, usage snippets). It acts as a Model‑Context‑Protocol (MCP) server, giving your AI assistant a structured way to discover libraries and integrate them quickly.