# GitHub AI Repositories Enricher (`viniman27/github-ai-repos-enricher`) Actor

Find and score public GitHub AI repositories for market research, lead discovery, and technical scouting using the public GitHub Search API.

- **URL**: https://apify.com/viniman27/github-ai-repos-enricher.md
- **Developed by:** [Vinicius Assumpção de Araujo](https://apify.com/viniman27) (community)
- **Categories:** Developer tools, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $50.00 / 1,000 enriched github repositories

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## GitHub AI Repositories Enricher

Find and score public GitHub AI repositories for market research, lead discovery, competitive intelligence, and technical scouting.

This Actor is designed to stay cheap: it uses GitHub's public Search API over HTTP. No browser. No proxy. No login required for small runs.

### What it returns

Each dataset item includes:

- repository name and URL
- owner and owner URL
- stars, forks, issues, language, license
- GitHub topics
- AI categories: `agent`, `llm`, `rag`, `evaluation`, `inference`, `automation`, `vision`
- opportunity score from 0–100
- concise commercial summary

### Use cases

- Track fast-growing AI open-source projects.
- Build lead lists around AI tooling maintainers.
- Monitor competitor ecosystems.
- Feed weekly market intelligence reports.
- Discover projects to sponsor, integrate, or acquire.

### Free-tier friendly defaults

Default runs request 25 repositories and use one GitHub API call.

For unauthenticated use, keep runs small. If you need higher rate limits, pass `GITHUB_TOKEN` as an Apify secret/environment variable rather than hard-coding it.

### Example input

```json
{
  "query": "topic:artificial-intelligence",
  "minStars": 100,
  "pushedSinceDays": 90,
  "language": "Python",
  "maxResults": 10,
  "sort": "stars",
  "order": "desc"
}
```

### Cost profile

HTTP-only. One GitHub Search API request per run in the current MVP. No proxy. No browser. Low memory footprint.

# Actor input Schema

## `query` (type: `string`):

GitHub repository search query. Keep it public and unauthenticated-friendly.

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

Adds stars:>=N to the query.

## `pushedSinceDays` (type: `integer`):

Only repositories pushed within this many days.

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

Optional GitHub language qualifier, e.g. Python, TypeScript, Go.

## `maxResults` (type: `integer`):

Keep small for free-tier friendly runs. Unauthenticated GitHub API is rate-limited.

## `sort` (type: `string`):

GitHub search sort.

## `order` (type: `string`):

Sort order.

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

Optional token for higher rate limits. Stored as Actor input only if you provide it; prefer Apify secrets/env vars.

## Actor input object example

```json
{
  "query": "topic:artificial-intelligence",
  "minStars": 50,
  "pushedSinceDays": 60,
  "maxResults": 25,
  "sort": "stars",
  "order": "desc"
}
```

# Actor output Schema

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

Dataset rows containing scored GitHub AI repositories.

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

Summary JSON stored in the default key-value store under SUMMARY.

# 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("viniman27/github-ai-repos-enricher").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("viniman27/github-ai-repos-enricher").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 '{}' |
apify call viniman27/github-ai-repos-enricher --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=viniman27/github-ai-repos-enricher",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/tAUYGuEtFurt7Evnv/builds/NBgettFn0bbrENb2E/openapi.json