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
관련 서버
Gemini Web Search
Performs web searches using the Gemini Web Search Tool via the local gemini-cli.
Expo MCP Server
Search and get recommendations from the official Expo documentation.
Simple arXiv
Search and retrieve academic papers from the arXiv repository via its API.
302AI Web Search
A web search server powered by the 302.AI API.
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
Simple Files Vectorstore
Provides semantic search across local files by creating vector embeddings from watched directories.
US Business Data MCP Server
Search US business entities across 17 states, building permits in 400+ cities, SEC filings, and SAM.gov contracts.
Embedding MCP Server
An MCP server powered by txtai for semantic search, knowledge graphs, and AI-driven text processing.
Polymarket Trading MCP
Trading intelligence tools for Polymarket prediction markets: Slippage estimation, liquidity scanning, arbitrage detection, price feeds, wallet intelligence, and portfolio risk.
Perplexity
Interacting with Perplexity