# Pangolinfo Amazon Data MCP (`pangolinfo/pangolinfo-apify-actors-1`) Actor

Call 19 official read-only Pangolinfo Amazon Data MCP tools for Amazon products, reviews, niches, AI Overview, trends, Alexa, maps, WIPO, and US litigation. Get structured, agent-ready results.

- **URL**: https://apify.com/pangolinfo/pangolinfo-apify-actors-1.md
- **Developed by:** [Charon Jiang](https://apify.com/pangolinfo) (community)
- **Categories:** MCP servers, E-commerce, Agents
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Pangolinfo Amazon Data MCP

Run the official **Pangolinfo Amazon Data MCP** from Apify and receive structured, automation-ready results in a Dataset. This Actor is an MCP client adapter—not a duplicate REST scraper. It connects to the fixed official hosted endpoint, discovers the live tool schema, calls one selected read-only tool, and preserves both native MCP content blocks and parsed data for agents, workflows, scheduled runs, webhooks, and API integrations.

Learn about [Amazon Data MCP](https://www.pangolinfo.com/amazon-data-mcp/), read the [agent connection guide](https://docs.pangolinfo.com/en-help-center/mcp/agents), or create an API key in the [Pangolinfo Console](https://tool.pangolinfo.com/).

### What you can build

- Research Amazon products, keyword search results, reviews, seller catalogs, Best Sellers, and New Releases.
- Discover niches and categories, traverse category trees, and resolve category paths in batch.
- Monitor Google AI Overview and SERP visibility or retrieve keyword trends.
- Study Amazon Alexa shopping recommendations and conversational share of voice.
- Search local maps and WIPO design records, with an optional US patent-litigation chain, from agent workflows.
- Schedule MCP calls in Apify and export results to JSON, CSV, webhooks, cloud storage, or another Actor.

### The 19 read-only business tools

**Amazon core:** `search_amazon`, `get_amazon_product`, `get_amazon_delivery_time`, `get_amazon_reviews`, `list_seller_products`, `list_category_products`, `scrape_url`.

**Category and niche intelligence:** `filter_niches`, `filter_categories`, `search_categories`, `get_category_children`, `get_category_paths`, `list_bestsellers`, `list_new_releases`.

**Search intelligence:** `ai_search`, `keyword_trends`, `search_amazon_alexa`.

**Maps and public records:** `search_local_maps`, `wipo_search`. When supported by the selected WIPO query, `enableLitigation` chains the related US litigation lookup into the same tool response.

The free `pangolinfo_capabilities` utility is also available for inspecting the server before a business data call; it is intentionally not counted among the 19 business tools.

### Input

1. Add your Pangolinfo API key to the secret input. Apify encrypts the field, and this Actor never writes the key to its Dataset or logs.
2. Select an MCP tool.
3. Enter the tool arguments as a JSON object. Keep **Verify the live tool schema** enabled so the Actor checks `tools/list` before `tools/call`.

Start safely with:

```json
{
  "toolName": "pangolinfo_capabilities",
  "toolArguments": {}
}
```

For a business call, choose a tool and use the argument names shown by its current live schema. Example Tasks published with this Actor provide tested inputs for common workflows such as product research, review analysis, niche discovery, AI Overview monitoring, and Alexa recommendation tracking.

### Output and reliability

Each successful run writes one Dataset item containing `toolName`, `calledAt`, `argumentKeys`, `attempts`, protocol provenance, the live `inputSchema`, original MCP `content`, optional `structuredContent`, and normalized `data`. Argument values are not copied into provenance metadata. The Actor uses MCP Streamable HTTP, enforces a fixed Pangolinfo endpoint and an explicit allowlist, validates the selected live tool, caps the timeout at five minutes, performs only bounded retries for transient failures, and redacts the API key from error text.

### Official resources

- [Pangolinfo Amazon Data MCP product page](https://www.pangolinfo.com/amazon-data-mcp/)
- [MCP documentation for agents](https://docs.pangolinfo.com/en-help-center/mcp/agents)
- [Open-source npm bridge](https://www.npmjs.com/package/pangolinfo-amazon-data-mcp)
- [GitHub repository](https://github.com/Pangolin-spg/amazon-data-mcp)
- [Smithery server page](https://smithery.ai/servers/pangolinfo/amazon-data)

Related data services include the [Amazon Scraper API](https://www.pangolinfo.com/amazon-scraper-api/), [Amazon Niche Data API](https://www.pangolinfo.com/amazon-niche-data-api/), [AI Overview SERP API](https://www.pangolinfo.com/ai-overview-serp-api/), and [Amazon Alexa API](https://www.pangolinfo.com/amazon-alexa-api/).

This official integration is maintained by Pangolinfo and released under the MIT License. Pangolinfo API usage is governed by the terms and plan associated with your own account.

# Actor input Schema

## `apiKey` (type: `string`):

Bearer API key from the Pangolinfo Console. Apify stores this field encrypted.

## `toolName` (type: `string`):

Choose one business tool, or inspect the free capabilities utility before a paid data call.

## `toolArguments` (type: `object`):

Arguments defined by the selected hosted MCP tool. Start with {} for the capabilities utility. Examples are documented in the README.

## `verifyToolSchema` (type: `boolean`):

Confirm the selected tool is advertised by the hosted MCP server before calling it. Recommended for reliable automations.

## `timeoutSeconds` (type: `integer`):

Maximum time for the MCP tool call. Data collection tools can take longer than ordinary HTTP requests.

## Actor input object example

```json
{
  "toolName": "pangolinfo_capabilities",
  "toolArguments": {},
  "verifyToolSchema": true,
  "timeoutSeconds": 180
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset item returned by the selected Pangolinfo MCP tool.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("pangolinfo/pangolinfo-apify-actors-1").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("pangolinfo/pangolinfo-apify-actors-1").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call pangolinfo/pangolinfo-apify-actors-1 --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,pangolinfo/pangolinfo-apify-actors-1"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/urZjSXthhLt6yWXum/builds/GlhfbNC3ZOh64XyhR/openapi.json