Real-time Amazon, WIPO & PACER data for AI agents — 19 tools via the MCP protocol.
Pangolinfo Amazon Data MCP Server (io.github.Pangolin-spg/pangolinfo-mcp)
This MCP server provides real-time Amazon, WIPO, and PACER data for AI agents via the Model Context Protocol (MCP). It exposes 19 tools through MCP, covering Amazon-related data categories described in its package excerpt.
🛠️ Key Features
Real-time Amazon, WIPO, and PACER data
Model Context Protocol (MCP) server
19 data tools available to MCP clients
Topics include AI agents, Amazon data, web scraping, and Python
🚀 Use Cases
Supplying Amazon/WIPO/PACER data to AI agents through MCP
Calling the same MCP tools from Python code
⚡ Developer Benefits
Python client to call MCP tools from code (no AI client required)
Single client access to all 19 Amazon/WIPO/PACER tools
⚠️ Limitations
Tool details beyond “19 tools” and the listed Amazon categories are not fully specified in the provided excerpt
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
code
pip install pangolinfo-mcp
Quick start
1. Get a permanent API key
Sign up at tool.pangolinfo.com and grab a permanent API key from Account Center.
2. Use the client
python
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
python
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
python
# 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.
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: