# Tech Adoption Tracker — GitHub Stars & npm Downloads (`inovaflow/tech-adoption-tracker`) Actor

Track developer adoption of any repo, package or app: GitHub stars, forks, contributors and releases, npm and PyPI download trends, App Store, Google Play and Chrome ratings. One typed row per entity with the change since your last run. Dataset-only, MCP-ready.

- **URL**: https://apify.com/inovaflow/tech-adoption-tracker.md
- **Developed by:** [inovaflow](https://apify.com/inovaflow) (community)
- **Categories:** Developer tools, Lead generation, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 entity observations

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Tech Adoption Tracker — GitHub Stars & npm Downloads

**If you sell to developers, adoption comes before revenue.** A competitor's SDK picks up 3,000 stars in a week, a
new framework doubles its npm downloads, a rival app starts climbing the App Store chart. Each of these shows up
in the adoption numbers weeks before it reaches a press release or a pricing page. Those numbers are spread
across five different sites, each with its own format. None of them tell you what changed since you last looked.

This Actor puts them in one place. Give it repos, packages, apps, GitHub organizations or just a topic, and every
run returns **one typed row per entity** with the current adoption metrics **and the change since your previous
run**. Put it on a schedule and you have a developer-adoption feed that your agent, dashboard or warehouse can
trend without any cleanup.

***

### Who it is for

- **DevRel and PLG teams**: track your own repos and packages next to your competitors' and see week-over-week
  momentum in one table.
- **AI and GTM agents**: one call, no login, no key. Every row has the same keys and only raw numbers, so the
  agent does the reasoning and nothing has to be parsed.
- **Founders and product marketers**: track which tools in your category are gaining stars and downloads, so
  you know who is actually winning.
- **VCs and analysts**: discover the most-adopted projects in a topic (`mcp`, `vector-database`, `llm`) and track
  them run over run.
- **Sales teams selling to dev-tool companies**: every row carries the owning company's domain, ready to join to
  your CRM.

***

### What makes it different

| | Typical GitHub or npm scraper | This Actor |
| --- | --- | --- |
| Coverage | one platform | **GitHub, npm, PyPI, Apple App Store, Google Play, Chrome Web Store**, in one run and one schema |
| Re-runs | the same snapshot again | **the change since your last run** for every metric, plus a new-release flag |
| First run | a snapshot | download trends from day one: this week, the previous week, and the difference |
| Company | a repo owner login | **the owning company's domain**, resolved conservatively and labelled with where it came from |
| Missing data | zero, or silently absent | `null`, and `unreadFields` tells you whether it was *not reported* or *not read this run* |
| Keys | none needed | none needed. An optional GitHub token only raises the rate limit |

***

### What you get per entity

Every row has the same shape. Metrics a platform does not report are `null`, never guessed and never zero.

```jsonc
// A real row: second run of a watch, a few minutes after the first
{
  "canonicalId": "github:supabase/supabase",
  "platform": "github",
  "entityId": "supabase/supabase",
  "name": "supabase",
  "owner": "supabase",
  "ownerType": "organization",
  "companyDomain": "supabase.com",
  "companyDomainSource": "github-org-website",
  "url": "https://github.com/supabase/supabase",
  "homepage": "https://supabase.com",
  "language": "TypeScript",
  "license": "Apache-2.0",
  "lastActivityAt": "2026-09-26T06:50:31Z",
  "metrics": {
    "stars": 110771, "forks": 14969, "watchers": 753, "openIssues": 1085, "contributors": 2049,
    "downloadsWeek": null, "rating": null /* … every metric key, null when it does not apply */
  },
  "deltas": { "stars": -1, "forks": 2, "watchers": 0, "openIssues": 0, "contributors": 0 /* … */ },
  "deltaWindowHours": 0.05,
  "latestRelease": {
    "version": "v1.26.08",
    "publishedAt": "2026-08-07T13:57:57Z",
    "notesExcerpt": "Here’s everything that happened with Supabase in the last month: ## Supabase Select SF 2026 …",
    "url": "https://github.com/supabase/supabase/releases/tag/v1.26.08"
  },
  "newReleaseSinceLastRun": false,
  "isBaseline": false,
  "previousObservedAt": "2026-09-26T08:32:28.074Z",
  "firstSeenAt": "2026-09-26T08:32:28.074Z",
  "observedAt": "2026-09-26T08:35:13.898Z",
  "runsObserved": 2,
  "discoveredVia": "github-org:supabase",
  "unreadFields": [],
  "watchId": "qa-mixed"
}
```

#### The metrics, by platform

| Platform | Metrics filled |
| --- | --- |
| **GitHub** repos | `stars`, `forks`, `watchers`, `openIssues` (GitHub counts open PRs here too), `contributors`, latest release with the maintainers' own notes |
| **npm** packages | `downloadsDay`, `downloadsWeek`, `downloadsPrevWeek`, `downloadsDelta` (week over week), `downloadsMonth` (30 days), latest version and its publish date, linked repo |
| **PyPI** packages | the same download windows (mirrors excluded), `versionsCount`, first and latest release dates, linked repo |
| **Apple App Store** | `rating`, `reviewCount`, `ratingCurrentVersion`, `reviewCountCurrentVersion`, `chartRank` (US top 100 overall), `categoryRank` (US top 100 in its category), version and release notes |
| **Google Play** | `rating`, `reviewCount`, `installsMin` (lower bound of the install bucket: 10B+ becomes 10000000000), last update |
| **Chrome Web Store** | `users`, `rating`, `reviewCount` (as the store displays it, e.g. 43.1K), version, last update |

`deltas` has the same keys as `metrics`: each metric now minus the same metric at the previous observation in this
watch. Packages also have `repository` (e.g. `github:vercel/ai`), so you can join a package row to its repo row.

#### Company domain: conservative by design

`companyDomain` is only filled from a field the owner controls: the GitHub **organization's** website, the
package's homepage, or the app developer's website. `companyDomainSource` says which one was used. Shared hosts
(github.io, readthedocs, social profiles) and personal accounts stay `null`. A missing domain costs your agent one
lookup. A wrong one sends outreach to the wrong company.

***

### How to use it

**Track a list.** Paste repos, packages and apps into their fields, or mix them all in *Anything else*:

```json
{
  "githubRepos": ["vercel/next.js", "langchain-ai/langchain"],
  "npmPackages": ["react", "@modelcontextprotocol/sdk"],
  "pypiPackages": ["requests", "fastapi"]
}
```

**Track a company's whole open-source footprint:** `"githubOrgs": ["supabase"]` adds its most-starred public repos.

**Discover a market:** `"topics": ["mcp"]` or `"keywords": ["ai agent framework"]` adds the most-starred GitHub
repos and the most-downloaded npm packages for each (narrow with `language` and `minStars`).

**Add apps:** App Store, Google Play and Chrome Web Store URLs or ids. Listing an app switches the app stores on.

**Schedule it.** Run it daily or weekly with the same input. The first run is the **baseline** (`isBaseline: true`,
deltas `null`). Every run after that reports the change. The trend memory is keyed by the **watch**: leave
`watchId` empty and it is derived from your list, or name it (`"watchId": "competitor-sdks"`) to share one
history across schedules or to start fresh.

#### Output views

- **All entities**: the headline numbers and deltas for everything.
- **GitHub repos**, **npm & PyPI packages**, **Apps & extensions**: one table per platform with every metric.
- **Run summary** (`OUTPUT` record): counts, top star, download and rating gains, new releases since the last
  run, anything skipped with the reason, and the discovery report.

***

### Good to know

- **No key needed.** Without a token, GitHub allows about 60 requests an hour per IP, and a repo costs about 3.
  When that runs out the Actor moves to a fresh IP and keeps going. For hundreds of repos per run, add a GitHub
  token (no scopes needed). It lifts the limit to 5,000 an hour and is stored encrypted.
- **Renamed or moved repos** follow the redirect. The row carries the new name, and `renamedFrom` has the one you
  gave.
- **Nothing is invented.** A package younger than a week has a `null` weekly figure, not a zero. A repo without
  releases has `latestRelease: null`. If something could not be read this run (a rate limit or timeout), it is
  listed in `unreadFields`.
- **Skipped entities are free.** Missing packages, removed apps and typos are listed in the run summary with the
  reason. They produce no row and no charge.
- PyPI has no public search, so discovery covers GitHub and npm. PyPI packages are tracked by name.

### Pricing

Pay per event: **$0.005 per entity observation** delivered to your dataset, plus the standard Actor start fee.
An empty run is never charged per row. A daily watch of 50 repos and packages costs about $0.25 a day.

### Use it from an AI agent (MCP)

The Actor is available through the Apify MCP server. An agent can call it with nothing more than
`{"npmPackages": ["zod"], "githubRepos": ["colinhacks/zod"]}`, get typed rows back, and call it again tomorrow
for the deltas.

# Actor input Schema

## `githubRepos` (type: `array`):

`owner/repo` or a GitHub URL, one per line — `vercel/next.js`, `https://github.com/langchain-ai/langchain`. Returns stars, forks, watchers, open issues, contributors and the latest release.

## `npmPackages` (type: `array`):

Package names or npmjs.com URLs, one per line — `react`, `@modelcontextprotocol/sdk`. Returns downloads for the last day, week, previous week and 30 days, plus the latest version and its publish date.

## `pypiPackages` (type: `array`):

Project names or pypi.org URLs, one per line — `requests`, `fastapi`. Returns downloads for the last day, week, previous week and 30 days (mirrors excluded), the version count and the latest release.

## `githubOrgs` (type: `array`):

Track a whole company's open source at once — organization logins or URLs, one per line (`vercel`, `https://github.com/supabase`). Each expands to its most-starred public repos (see the per-organization limit below).

## `entities` (type: `array`):

Mix any identifiers in one list and the Actor works out the platform: repo, npm, PyPI, App Store, Google Play or Chrome Web Store URLs, or prefixed ids like `npm:zod`, `pypi:pydantic`, `github:owner/repo`, `org:stripe`, `apple:310633997`, `play:com.whatsapp`, `chrome:<extension id>`.

## `topics` (type: `array`):

GitHub topics and npm keywords, one per line — `mcp`, `vector-database`, `llm`. Matches the tags maintainers put on their own projects.

## `keywords` (type: `array`):

Free-text searches, one per line — `ai agent framework`, `feature flags`. Matched against GitHub repo names, descriptions and topics, and npm package text.

## `language` (type: `string`):

Only discover GitHub repos written in this language — `TypeScript`, `Python`, `Go`, `Rust`.

## `minStars` (type: `integer`):

Skip discovered repos below this star count, to leave out toy projects.

## `maxPerDiscovery` (type: `integer`):

How many repos and packages each topic or keyword adds, most-adopted first.

## `maxReposPerOrg` (type: `integer`):

How many of each organization's most-starred public repos to track (forks and archived repos left out).

## `appStoreApps` (type: `array`):

App Store URLs, numeric app ids (`310633997`) or bundle ids, one per line. Returns the rating and rating count (overall and for the current version), the US top-100 chart position overall and in the app's category, and the latest version with its release notes.

## `googlePlayApps` (type: `array`):

Google Play URLs or package ids (`com.whatsapp`), one per line. Returns the rating, rating count, install bucket (lower bound, e.g. 10B+ → 10000000000) and last update date.

## `chromeExtensions` (type: `array`):

Chrome Web Store URLs or 32-letter extension ids, one per line. Returns users, rating, rating count, version and last update date.

## `watchId` (type: `string`):

Runs with the same watch name compare against each other. Leave empty and the Actor derives one from what you track, so a scheduled run with the same input keeps its history automatically. Name it when several schedules share one list, or to start a fresh baseline.

## `maxEntities` (type: `integer`):

Upper bound on entities observed and charged in one run — the listed ones first, then organization repos, then discoveries.

## `sources` (type: `array`):

Leave empty for GitHub, npm and PyPI — plus the app stores whenever you list an app. Pick platforms here to restrict a mixed list or the discovery to them.

## `includeContributors` (type: `boolean`):

One extra GitHub request per repo. Very large monorepos report no count (GitHub refuses to list them) and return null.

## `includeReleases` (type: `boolean`):

Version, date and the maintainers' own release notes (trimmed) of each repo's latest release. One extra GitHub request per repo.

## `resolveCompanyDomains` (type: `boolean`):

Read the website of the GitHub organization behind each repo or package, so each row carries the company domain for joining to your CRM. One GitHub request per distinct organization.

## `githubToken` (type: `string`):

Not needed — the Actor works without one. A personal access token with no scopes raises GitHub's limit from 60 to 5,000 requests an hour, for lists of hundreds of repos. Stored encrypted, used only for api.github.com.

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

Entities read at the same time.

## Actor input object example

```json
{
  "githubRepos": [
    "vercel/next.js",
    "langchain-ai/langchain"
  ],
  "npmPackages": [
    "react",
    "@modelcontextprotocol/sdk"
  ],
  "pypiPackages": [
    "requests",
    "fastapi"
  ],
  "githubOrgs": [
    "supabase"
  ],
  "entities": [
    "npm:zod",
    "pypi:pydantic",
    "https://github.com/supabase/supabase"
  ],
  "topics": [
    "mcp",
    "vector-database"
  ],
  "keywords": [
    "ai agent framework"
  ],
  "language": "TypeScript",
  "minStars": 500,
  "maxPerDiscovery": 10,
  "maxReposPerOrg": 10,
  "appStoreApps": [
    "https://apps.apple.com/us/app/whatsapp-messenger/id310633997"
  ],
  "googlePlayApps": [
    "com.whatsapp"
  ],
  "chromeExtensions": [
    "https://chromewebstore.google.com/detail/grammarly-ai-writing-assi/kbfnbcaeplbcioakkpcpgfkobkghlhen"
  ],
  "watchId": "competitor-sdks",
  "maxEntities": 100,
  "includeContributors": true,
  "includeReleases": true,
  "resolveCompanyDomains": true,
  "maxConcurrency": 4
}
```

# Actor output Schema

## `entities` (type: `string`):

One row per repo, package or app: headline metrics, change since the previous run, company domain.

## `github` (type: `string`):

Stars, forks, watchers, issues, contributors and the latest release, with deltas.

## `packages` (type: `string`):

Daily, weekly, previous-week and 30-day downloads, the latest version, with deltas.

## `apps` (type: `string`):

Rating, rating count, installs or users and US chart rank, with deltas.

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

Counts, top star / download / rating gains, new releases, skipped entities with reasons, discovery report, GitHub rate-limit usage and the watch id.

# 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 = {
    "githubRepos": [
        "vercel/next.js",
        "langchain-ai/langchain"
    ],
    "npmPackages": [
        "react",
        "@modelcontextprotocol/sdk"
    ],
    "pypiPackages": [
        "requests",
        "fastapi"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("inovaflow/tech-adoption-tracker").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 = {
    "githubRepos": [
        "vercel/next.js",
        "langchain-ai/langchain",
    ],
    "npmPackages": [
        "react",
        "@modelcontextprotocol/sdk",
    ],
    "pypiPackages": [
        "requests",
        "fastapi",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("inovaflow/tech-adoption-tracker").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 '{
  "githubRepos": [
    "vercel/next.js",
    "langchain-ai/langchain"
  ],
  "npmPackages": [
    "react",
    "@modelcontextprotocol/sdk"
  ],
  "pypiPackages": [
    "requests",
    "fastapi"
  ]
}' |
apify call inovaflow/tech-adoption-tracker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,inovaflow/tech-adoption-tracker"
        }
    }
}
```

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/JVokqDNnvu4T05g31/builds/ZDbbf8echCkBxFuHR/openapi.json