Pangolinfo Amazon MCP

Real-time Amazon data MCP for products, reviews, search and best sellers across 20+ marketplaces.

Documentation

pangolinfo-mcp

Python client for the Pangolinfo Amazon Data MCP server — 19 Amazon / WIPO / PACER data tools callable from Python, no AI client required.

Built and maintained by PANGOLIN INFO TECH PTE. LTD.

Why this package

The Amazon Data MCP gives AI agents 19 data tools via the MCP protocol. This package lets Python developers call those same tools from code — no Claude, Cursor, or any AI client needed.

19 tools in one client: Amazon product, reviews, search, niches, bestsellers, AI SERP, WIPO, PACER and more
Zero dependencies beyond httpx — no MCP SDK required
Sync interface (async coming soon)
Same engine, same pricing as the REST API and MCP server

Installation

pip install pangolinfo-mcp

Quick start

1. Get a permanent API key

2. Use the client

from pangolinfo_mcp import PangolinfoMCPClient

client = PangolinfoMCPClient(api_key="your_permanent_api_key")

# Amazon product detail
product = client.get_amazon_product("B0DYTF8L2W")
print(product["title"])

# Keyword search
results = client.search_amazon("wireless earbuds")

# Best sellers in a category
bestsellers = client.list_bestsellers(category_id="172282")

# WIPO trademark check
trademarks = client.wipo_search("Nike")

# PACER patent litigation
cases = client.pacer_search("Apple Inc.")

# List all available tools
tools = client.list_tools()

client.close()

Context manager

with PangolinfoMCPClient(api_key="your_key") as client:
    product = client.get_amazon_product("B0DYTF8L2W")

All 19 tools

Amazon Core Data (5)

Method	Description
`client.search_amazon(keyword)`	Search Amazon products
`client.get_amazon_product(asin)`	Full product detail
`client.get_amazon_reviews(asin)`	Paginated reviews
`client.list_seller_products(seller_id)`	Seller storefront
`client.scrape_url(url)`	Scrape any Amazon page

Category & Niche Analysis (8)

Method	Description
`client.filter_niches(**metrics)`	Blue-ocean niche discovery
`client.filter_categories(**metrics)`	Category filtering
`client.search_categories(query)`	Full-text category search
`client.get_category_children(node_id)`	Browse node children
`client.get_category_tree()`	Root category tree
`client.batch_category_paths(category_ids)`	Batch category paths
`client.list_bestsellers(category_id)`	Best Sellers list
`client.list_new_releases(category_id)`	New Releases list

Search & SERP AI (3)

Method	Description
`client.ai_search(query)`	AI Overview / AI Mode SERP
`client.keyword_trends(keyword)`	Keyword trend time-series
`client.search_amazon_alexa(query)`	Alexa for Shopping

Maps & IP Compliance (3)

Method	Description
`client.search_local_maps(query)`	Maps POI data
`client.wipo_search(keyword)`	WIPO trademark search
`client.pacer_search(query)`	PACER patent litigation

Utility (1)

Method	Description
`client.capabilities()`	List all live tools (free)

Generic tool call

# Call any tool by name
result = client.call_tool("search_amazon", {"keyword": "laptop", "page": 2})

Use as an MCP server

This repo also documents the hosted MCP server that any MCP-compatible client (Claude Desktop, Cursor, VS Code, etc.) can connect to directly over Streamable HTTP — no local install required.

Add to your client's mcp.json / MCP config:

{
  "mcpServers": {
    "pangolinfo": {
      "url": "https://mcp.pangolinfo.com/mcp",
      "headers": {
        "Authorization": "Bearer pgl_your_api_key"
      }
    }
  }
}

Or pass the key inline as a query parameter:

https://mcp.pangolinfo.com/mcp?api_key=pgl_your_api_key

Get a permanent API key at tool.pangolinfo.com. The key is sent as a Bearer token; config is not hot-reloaded, so restart/reconnect the client after changing it.

For MCP clients that require a local stdio process, use the official npm bridge:

PANGOLINFO_API_KEY="your_key" npx -y pangolinfo-amazon-data-mcp

Source and client configuration: github.com/Pangolin-spg/amazon-data-mcp.