# GitHub Trending and Repo Mover Tracker (`scrapemint/github-trending-scraper`) Actor
Pull the GitHub trending list for any timeframe, programming language, or spoken language. Each row carries owner, name, description, total stars, stars added in period, forks, language, and top contributors. JSON. Pay per repo.
- **URL**: https://apify.com/scrapemint/github-trending-scraper.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Developer tools, Business
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
$10.00 / 1,000 trending repo rows
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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use 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
## GitHub Trending and Repo Mover Tracker
Pull the GitHub trending list for any timeframe, programming language, or spoken language. Each row ships the owner, repo name, description, primary language, total stars, stars added in the active window, fork count, and the row of top contributors. Pay per repo. No auth required.
**Built for** investors scouting open source momentum, recruiters watching breakout projects, dev tool founders studying competitive launches, and content teams building "what's hot in OSS this week" newsletters.
**Keywords this actor ranks for:** github trending api, github trending intelligence, github trending json, pull github repos, github mover tracker, github stars tracker, oss momentum tracker, open source intelligence, oss investment scout, github watch list builder, top github repos api, trending repos by language.
---
### Why this actor
| Other GitHub trending tools | **This actor** |
|---|---|
| One web page that scrolls forever | Structured JSON one row per repo |
| All time only | Daily, weekly, and monthly windows |
| English only authors | Filter by spoken language code |
| Drop the contributor row | Top contributor avatars and handles included |
| Drop the period star count | "Stars added this week" parsed as a discrete field |
---
### How it works
```mermaid
flowchart LR
A[Timeframes + languages] --> B[github.com/trending
plus filter slugs]
B --> C[Plain server rendered HTML
no auth, no JS]
C --> D[Parse repo rows]
D --> E[Push one row per repo]
E --> F[(JSON CSV Excel API)]
````
Plain HTML, no browser needed. Cheerio parses the trending page and extracts each repo row with owner, name, description, language, stars, forks, and contributor avatars. Datacenter proxy is enough.
***
### What you get per row
```mermaid
flowchart LR
R[Repo row] --> R1[Identity
fullName owner name url]
R --> R2[Pitch
description language]
R --> R3[Momentum
starsTotal starsInPeriod forks]
R --> R4[Slice
timeframe languageFilter spokenLanguageCode]
R --> R5[People
builtBy contributor row]
```
***
### Quick start
**Daily trending across all languages**
```json
{
"timeframes": ["daily"]
}
```
**Weekly trending in TypeScript and Rust**
```json
{
"timeframes": ["weekly"],
"languages": ["typescript", "rust"]
}
```
**Monthly trending repos from Chinese authors**
```json
{
"timeframes": ["monthly"],
"spokenLanguageCode": "zh"
}
```
**Daily and weekly across Python and Go (4 lists per run)**
```json
{
"timeframes": ["daily", "weekly"],
"languages": ["python", "go"]
}
```
***
### Sample output
```json
{
"rank": 1,
"fullName": "anthropic/claude-code",
"owner": "anthropic",
"name": "claude-code",
"url": "https://github.com/anthropic/claude-code",
"description": "The official CLI for Claude",
"language": "TypeScript",
"languageColor": "#3178c6",
"starsTotal": 12500,
"starsInPeriod": 1230,
"forks": 850,
"timeframe": "daily",
"languageFilter": "typescript",
"spokenLanguageCode": null,
"builtBy": [
{ "username": "alice", "profileUrl": "https://github.com/alice", "avatarUrl": "https://avatars.githubusercontent.com/u/123" }
],
"scrapedAt": "2026-05-08T10:00:00.000Z"
}
```
***
### Who uses this
| Role | Use case |
|---|---|
| OSS investor | Scout breakout repos by language and momentum window before VCs do |
| Recruiter | Source senior engineers from the contributor row of trending repos |
| Dev tool founder | Watch competitive launches at the moment they hit the front page |
| Content team | Build a weekly "what's hot in OSS" newsletter from real data, not guesswork |
| Analyst | Track language adoption shifts week over week |
| Recruiter agency | Build prospect lists by language and spoken language for niche searches |
***
### Input reference
| Field | Type | What it does |
|---|---|---|
| `timeframes` | string\[] | One or more of daily, weekly, monthly. Default daily. |
| `languages` | string\[] | Programming language slugs to filter by. Empty means all languages. |
| `spokenLanguageCode` | string | Two letter ISO code, for example en or zh. |
| `maxReposPerList` | integer | Cap per timeframe and language combination. Max 25. |
| `includeContributors` | boolean | Include the "Built by" avatar row with username and profile URL. |
| `proxyConfiguration` | object | Apify proxy. Datacenter is fine for GitHub. |
***
### API call
```bash
curl -X POST \
"https://api.apify.com/v2/acts/YOUR_USER~github-trending-scraper/runs?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"timeframes": ["daily", "weekly"],
"languages": ["python", "rust"]
}'
```
***
### Pricing
The first 5 repos per run are free so you can validate output before paying. After that, each repo row is charged. No surprise add on charges.
***
### FAQ
#### Do I need a GitHub token?
No. The actor only touches the public trending HTML page that any anonymous web visitor can see.
#### How many repos does each list return?
GitHub trending shows up to 25 repos per timeframe and language combination. The actor returns up to that cap per list.
#### Can I pull historical trending data?
GitHub does not publish a historical trending archive. Schedule the actor on a daily cron and store snapshots yourself to build your own time series.
#### How fresh is the data?
Each run hits the live trending page, so star counts and the contributor row reflect what GitHub renders at pull time.
#### Can I track a specific repo over time?
Run the actor on a schedule and filter the resulting dataset by `fullName`. Combine with the Apify scheduler to get a daily or weekly snapshot per repo.
#### Is pulling GitHub trending allowed?
This actor reads HTML any anonymous web visitor can see. Respect GitHub's terms and rate limit sensibly.
***
### Related actors
- **GitHub Issue Monitor** , track new issues and PR activity on a watch list of repos
- **HN Lead Monitor** , Hacker News mentions and high intent leads
- **Stack Overflow Lead Monitor** , track buyer questions across tags
- **ProductHunt Launch Tracker** , launches by topic with maker info parsed
- **LinkedIn Pulse Articles Intelligence** , long form content intelligence for thought leadership tracking
# Actor input Schema
## `timeframes` (type: `array`):
Which trending windows to scrape. Pick any of daily, weekly, monthly.
## `languages` (type: `array`):
Filter trending by programming language slug. Examples: 'python', 'typescript', 'rust', 'go'. Leave empty to scrape the all languages list.
## `spokenLanguageCode` (type: `string`):
Filter by author's spoken language. Two letter ISO code, for example 'en' or 'zh'. Leave empty for all.
## `maxReposPerList` (type: `integer`):
Hard cap per timeframe and language combination. GitHub trending shows up to 25 repos per list. 0 means take everything.
## `includeContributors` (type: `boolean`):
Pull the small avatars under each repo (the 'Built by' row) with username and profile URL.
## `proxyConfiguration` (type: `object`):
Apify proxy. Datacenter is fine for GitHub trending.
## Actor input object example
```json
{
"timeframes": [
"daily"
],
"languages": [],
"spokenLanguageCode": "",
"maxReposPerList": 25,
"includeContributors": true,
"proxyConfiguration": {
"useApifyProxy": true
}
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"proxyConfiguration": {
"useApifyProxy": true
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/github-trending-scraper").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "proxyConfiguration": { "useApifyProxy": True } }
# Run the Actor and wait for it to finish
run = client.actor("scrapemint/github-trending-scraper").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 '{
"proxyConfiguration": {
"useApifyProxy": true
}
}' |
apify call scrapemint/github-trending-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapemint/github-trending-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "GitHub Trending and Repo Mover Tracker",
"description": "Pull the GitHub trending list for any timeframe, programming language, or spoken language. Each row carries owner, name, description, total stars, stars added in period, forks, language, and top contributors. JSON. Pay per repo.",
"version": "0.1",
"x-build-id": "QzjRmQIBqbvUNOhwv"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapemint~github-trending-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapemint-github-trending-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapemint~github-trending-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapemint-github-trending-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapemint~github-trending-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapemint-github-trending-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"timeframes"
],
"properties": {
"timeframes": {
"title": "Timeframes",
"uniqueItems": true,
"type": "array",
"description": "Which trending windows to scrape. Pick any of daily, weekly, monthly.",
"items": {
"type": "string",
"enum": [
"daily",
"weekly",
"monthly"
],
"enumTitles": [
"Daily (last 24 hours)",
"Weekly (last 7 days)",
"Monthly (last 30 days)"
]
},
"default": [
"daily"
]
},
"languages": {
"title": "Programming languages",
"type": "array",
"description": "Filter trending by programming language slug. Examples: 'python', 'typescript', 'rust', 'go'. Leave empty to scrape the all languages list.",
"default": [],
"items": {
"type": "string"
}
},
"spokenLanguageCode": {
"title": "Spoken language code",
"type": "string",
"description": "Filter by author's spoken language. Two letter ISO code, for example 'en' or 'zh'. Leave empty for all.",
"default": ""
},
"maxReposPerList": {
"title": "Max repos per list",
"minimum": 0,
"maximum": 25,
"type": "integer",
"description": "Hard cap per timeframe and language combination. GitHub trending shows up to 25 repos per list. 0 means take everything.",
"default": 25
},
"includeContributors": {
"title": "Include top contributors",
"type": "boolean",
"description": "Pull the small avatars under each repo (the 'Built by' row) with username and profile URL.",
"default": true
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Apify proxy. Datacenter is fine for GitHub trending.",
"default": {
"useApifyProxy": true
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```