# Multi-Source Trending Snapshot (`jiangzhang/multi-source-trending-snapshot`) Actor

One run returns a cross-source snapshot as a single table: fastest-rising new GitHub repos, Hugging Face models by trending score, and the latest arXiv cs.AI papers. Unified fields, so you compare across sources, not three scrapers.

- **URL**: https://apify.com/jiangzhang/multi-source-trending-snapshot.md
- **Developed by:** [Jiang Zhag](https://apify.com/jiangzhang) (community)
- **Categories:** AI, Developer tools, News
- **Stats:** 2 total users, 1 monthly users, 100.0% 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?

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

## Multi-Source Trending Snapshot

One run → **one comparable table** from three sources:

| source | what you get | score field |
|---|---|---|
| `github` | fastest-rising **new** repos (created within N days, sorted by stars) | stars |
| `huggingface` | models sorted by Hugging Face **trending score** | trendingScore |
| `arxiv` | latest **cs.AI** papers (title, authors, abstract, link) | published date |

Every row shares the same shape, so you can filter/sort across sources in one pass:

```json
{"source": "github", "kind": "repo", "title": "owner/name",
 "url": "https://github.com/owner/name", "score": 24544, "score_label": "stars",
 "extra": {"language": "C++", "forks": 2494, "description": "..."},
 "collected_at": "2026-10-14T21:44:16+00:00"}
```

### Input

- `sources` — any subset of `github`, `huggingface`, `arxiv` (default: all three)
- `maxItemsPerSource` — default 20
- `sinceDays` — for GitHub only: only repos created in the last N days (default 30)

### Why three sources in one actor

Most scrapers here cover a single source. If you need "what is actually trending right now"
in one pipeline, you otherwise run and join three different actors with three different schemas.
This returns a single dataset with unified fields.

### Notes

- Uses public APIs only (GitHub Search API, Hugging Face API, arXiv Atom API). No login required.
- If one source fails, the run still returns the others — and the failure is logged, never silent.

### Free version of a larger pipeline

This Actor is the free snapshot: three sources, unified fields, no key, no account.
The same collection pipeline also publishes these, if you need more:

- **Free daily digest** — 4 signals a day, every edition archived: https://data.jiangzhang.ca/signals4/latest.html
- **Full raw archive** (every day's snapshot as JSONL, CC BY 4.0): https://github.com/jiangzhangcc-glitch/ai-signals-daily
- **More sources and history** — 8 sources instead of 3, four updates a day, stable API key: https://data.jiangzhang.ca/signals4/go?to=landing\&src=apify
- **Pay once, CA$5** — the compiled dataset bundle (single JSONL, indexed SQLite, tidy daily entity CSV), refreshed daily: https://buy.stripe.com/00w28r4W08qq8CcecHgw008?client_reference_id=apify

*Data here is collected from public APIs and links to each original source. The mirrors above are CC BY 4.0 with attribution to "Signals 4 (Signals API)".*

# Actor input Schema

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

Which sources to collect in one run.

## `maxItemsPerSource` (type: `integer`):

How many items to take from each source.

## `sinceDays` (type: `integer`):

For GitHub only: include repos created in the last N days.

## Actor input object example

```json
{
  "sources": [
    "github",
    "huggingface",
    "arxiv"
  ],
  "maxItemsPerSource": 20,
  "sinceDays": 30
}
```

# Actor output Schema

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

All collected rows in the default dataset. Fields: source, kind, title, url, score, score_label, collected_at, extra.

# 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("jiangzhang/multi-source-trending-snapshot").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("jiangzhang/multi-source-trending-snapshot").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 jiangzhang/multi-source-trending-snapshot --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,jiangzhang/multi-source-trending-snapshot"
        }
    }
}
```

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/5gvTPL6nTjcfIFtM6/builds/WAoJ8Z2rbAuMbBIhV/openapi.json