About Pangolinfo
Live Amazon data for products, workflows, and AI
Pangolinfo turns continuously changing Amazon pages into structured data, so developers, ecommerce teams, and AI agents can integrate, analyze, and act faster.
No credit card · First 60 requests free · Test with live data
Supporting ecommerce, developer, and AI teams worldwide
Why we built Pangolinfo
Markets keep moving. Your data should not stand still.
Prices, ranks, ads, inventory, reviews, and bestseller lists never stop changing. Opening a page is easy. Keeping the same data usable, comparable, and production-ready across markets, locations, and time is the real challenge.
What we believe: First-hand data creates value only when it reaches a product, workflow, or decision.
Pages keep changing
Dynamic rendering, page structures, and access conditions turn in-house collection into a constant maintenance job.
Context changes the result
Marketplace, postal code, delivery location, and page type can change price, ads, inventory, and search results.
Data has to reach action
JSON, spreadsheets, and reports are not the finish line. Changes matter when they reach an application, agent, or team workflow.
What we built
One Amazon data foundation. Four ways to use it.
Your team should not rebuild the same data capability for every delivery method. Pangolinfo gives code, AI, and operational workflows one live data foundation.
One access, rendering, parsing, and validation layer
REST APIs
Bring live Amazon data into applications, data pipelines, and high-volume automation.
Explore Scraper API →MCP Servers
Let MCP-compatible AI agents call live Amazon data tools directly.
Explore Amazon Data MCP →AI Skills
Run product, review, keyword, and market analysis through natural language.
Use Amazon Scraper Skill →AMZ Data Tracker
Schedule collection and send current data to Lark Base and other team workspaces without maintaining code.
Explore AMZ Data Tracker →Why Amazon-native
Built for Amazon context, not generic pages
The same ASIN, keyword, or category can mean something different across marketplaces, postal codes, times, and positions on the page. Pangolinfo is built around those differences.
Explore Amazon data solutions →Page semantics
Products, search, reviews, sellers, bestseller lists, and new releases each have their own fields and business relationships.
Market context
Marketplace, postal code, currency, delivery location, and local results stay attached to every request.
Commercial signals
Organic rank, ad placement, price, inventory, Buy Box, BSR, and review changes remain explainable.
Reliability over time
We maintain access, rendering, parsing, and field validation so your team can focus on its own product and rules.
Production evidence
Proof from running systems, not vague claims
These figures come from Pangolinfo's current public product information and customer cases. Actual results vary by page, parameters, and use case.
Public figures checked in September 2026. Success rate is not an unconditional guarantee for every target or configuration.
High-volume Amazon data for an internal ERP
Standardized JSON and multi-market collection reduce parser maintenance, leaving the data team focused on its business model.
View API case studies →Best sellers, new releases, and reviews flow into Lark Base
AMZ Data Tracker connects scheduled collection with team tables, filtering rules, and AI analysis.
View the Tracker workflow →Let agents reason from current evidence
Instead of copying pages or preparing data by hand, agents can call structured Amazon tools through MCP.
Explore Amazon Data MCP →How data becomes useful
From page signal to business action
Pangolinfo handles the data infrastructure. You keep control of what to collect, how to apply your rules, and where the result goes.
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01
Define the target
Choose ASINs, keywords, categories, lists, sellers, or reviews.
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02
Access and parse
Handle proxies, CAPTCHAs, dynamic rendering, and Amazon page structures.
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03
Structure and validate
Return consistent fields while retaining marketplace, postal code, and page context.
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04
Deliver to action
Send results to a product, agent, database, webhook, or team table.
Who we serve
One live data foundation, built for different ways of working
BUILDERS
Data product and SaaS teams
Bring product, rank, ad, and review data into the software customers already use without maintaining proxies, browsers, or parsers.
- Stable schema
- Batch and concurrency
- Multi-market context
OPERATORS
Ecommerce operations and research teams
Monitor changes in new releases, prices, ranks, ads, and reviews, then route signals that match your rules to the right owner.
- Scheduled monitoring
- Historical records
- Team collaboration
AI TEAMS
AI product and agent teams
Give models current first-hand evidence during research, analysis, and execution instead of relying on stale model memory.
- MCP tool calls
- Skills workflows
- Traceable data inputs
Responsibility and boundaries
Trust means more than returning a response
We provide infrastructure for accessing public data and support responsible use through product controls, account management, and contractual terms. You choose the collection target and business purpose; Pangolinfo handles access, parsing, and structured delivery within the agreed scope.
For privacy, data processing, service scope, and usage restrictions, refer to the applicable policies and agreements.
Our journey
Built in Singapore for teams around the world
Pangolinfo was founded on November 11, 2022. We began with the access and parsing problems behind live Amazon data, then expanded the product around the ways teams actually use that data.
SINGAPORE · GLOBAL
Turn changing pages into data you can keep using
A single scrape is not the hard part. The challenge is delivering consistent, explainable data while marketplaces, locations, page structures, and access conditions keep changing. Pangolinfo brings access, rendering, Amazon-native parsing, and quality validation into one infrastructure layer.
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Pangolinfo is founded
We set out to reduce the repeated engineering behind proxies, browser rendering, page parsing, and field maintenance for live Amazon data.
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REST API
Amazon data becomes programmable
We launched REST APIs that turn product, search, list, review, and seller pages into structured outputs for applications and data pipelines.
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MCP · AI SKILLS
AI gets direct access to first-hand evidence
We extended beyond code-first interfaces with MCP Servers and AI Skills, enabling agents and analysis workflows to retrieve current Amazon data on demand.
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AMZ DATA TRACKER
Scheduled collection reaches team workspaces
AMZ Data Tracker added a no-maintenance route for sending list, product, rank, and review changes into Lark Base and the tools teams already use.
Preserve first-hand signals
Deliver structured page data so customers can build their own metrics, models, and strategy.
Design for continuous operation
One successful request is only the start. Long-term utility depends on parsing, validation, and engineering response.
Fit data to the way teams work
Developers, agents, and business teams can choose the shortest route instead of adapting to one tool.
Before you start
Clear answers to the questions that matter
Before choosing a data partner, you should know what it provides, where its boundaries are, and how to validate it with minimal commitment.
Have a technical question? Read the docs →Is Pangolinfo a seller tool or data infrastructure?
Pangolinfo is data infrastructure. REST APIs serve products and data pipelines; MCP and Skills serve AI workflows; AMZ Data Tracker supports continuous monitoring and team collaboration without maintaining code.
Is the data collected live or served from a prebuilt database?
The core API is designed to access current pages on demand and return structured results. It is not the same as a static database refreshed once a day. Product documentation and plan details define the applicable caching, response, and update behavior.
How should I choose between API, MCP, Skill, and Tracker?
Choose the API for products or high-volume pipelines; MCP when an agent should call tools autonomously; a Skill for guided natural-language analysis; and AMZ Data Tracker for scheduled monitoring and delivery into Lark Base or another team workspace.
Does Pangolinfo support different Amazon marketplaces and local results?
Relevant products support multiple Amazon marketplaces and can request specific market context through marketplace and postal-code parameters. Refer to the latest documentation for available marketplaces, postal codes, and parsers.
Can I test Pangolinfo without contacting sales?
Yes. Create an account to receive free requests and validate the service with a real ASIN, keyword, or page. Choose a suitable plan later if you need more volume, team capabilities, or custom delivery.
Start with one real request
Get to know Pangolinfo through live Amazon data
Use a real ASIN, keyword, or bestseller list to validate freshness, fields, and delivery before deciding which route fits your team.
