# npm Package Market Intelligence (`glowing_glove/npm-package-market-intelligence`) Actor

Research npm packages and categories with download counts, maintainers, versions, licenses, repository links, and package discovery signals.

- **URL**: https://apify.com/glowing\_glove/npm-package-market-intelligence.md
- **Developed by:** [Ushba Khan](https://apify.com/glowing_glove) (community)
- **Categories:** Developer tools, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$16.00 / 1,000 processed package queries

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## 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

## npm Package Market Intelligence

Research npm packages and categories with download counts, maintainers, versions, licenses, repository links, and package discovery signals.

This actor is designed for clean business-ready output. It avoids raw page dumps and returns one compact row per input with the most useful extracted signals and a short recommended next action.

### Input

Use `packagesOrQueries` for the main values. Keep `maxItems` modest for quick checks, then increase it for scheduled monitoring or larger research runs.

### Output

Each dataset row includes:

- the original input and status
- a capped list of the most relevant items
- counts, dates, scores, themes, or gaps where useful
- a practical next action
- timestamps for monitoring workflows

### Common use cases

- competitor research
- lead generation
- market monitoring
- product and content planning
- security, finance, or developer ecosystem intelligence

### Pricing

Recommended Pay Per Event pricing: `processedPackageQuery` at **$0.016 per processed package query**.

Charge only when an input is processed and a dataset row is delivered.

# Actor input Schema

## `packagesOrQueries` (type: `array`):

Add one or more values to process. Start with a small list, then scale once the output looks right.

## `maxItems` (type: `integer`):

Caps nested reviews, videos, repositories, packages, questions, filings, or vulnerabilities per input row.

## `requestTimeoutSecs` (type: `integer`):

Timeout for each public request in seconds.

## `maxConcurrency` (type: `integer`):

How many inputs to process at the same time.

## `proxyConfiguration` (type: `object`):

Optional Apify Proxy configuration for stricter public sources.

## Actor input object example

```json
{
  "packagesOrQueries": [
    "apify",
    "openai agents"
  ],
  "maxItems": 10,
  "requestTimeoutSecs": 25,
  "maxConcurrency": 3,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

No description

## `summary` (type: `string`):

No description

# 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 = {
    "packagesOrQueries": [
        "apify",
        "openai agents"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("glowing_glove/npm-package-market-intelligence").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 = { "packagesOrQueries": [
        "apify",
        "openai agents",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("glowing_glove/npm-package-market-intelligence").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "packagesOrQueries": [
    "apify",
    "openai agents"
  ]
}' |
apify call glowing_glove/npm-package-market-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=glowing_glove/npm-package-market-intelligence",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/bo5X0q5wU29fx3qyG/builds/7f4kBgxxg7ce1tPh2/openapi.json