# GitHub Issues Scraper – Repo Issues & Labels (`devil_port369-owner/github-issues-scraper`) Actor

Scrape public GitHub repository issues without a token. Title, body, state, labels, author, comments count, and emails from body. Streams linear JSON rows page by page.

- **URL**: https://apify.com/devil\_port369-owner/github-issues-scraper.md
- **Developed by:** [DataFusionX](https://apify.com/devil_port369-owner) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

### What does GitHub Issues Scraper do?

**GitHub Issues Scraper extracts every issue from any public GitHub repository — title, state, labels, author, comment counts, and full body text — from a repo URL or `owner/repo` string.** It's built for open-source maintainers, engineering managers, and support/DevRel teams who need structured issue data for triage, reporting, or trend analysis without manually paging through GitHub's issues tab. Unlike the raw GitHub API — which mixes issues and pull requests together and enforces strict pagination — this Actor filters PRs out by default, supports open/closed/all state filtering, and batches multiple repositories in a single run with no personal access token required.

### Why scrape GitHub issues? (Business Use Cases)

- **Bug & Backlog Triage at Scale** — Pull every open issue with labels and comment counts to prioritize engineering backlog or spot recurring bug patterns across releases.
- **Competitive & Product Intelligence** — Monitor issues filed against competitor or partner open-source tools to understand pain points, feature gaps, and user sentiment.
- **Community & DevRel Reporting** — Track issue volume, resolution time, and label distribution to report on open-source community health and maintainer responsiveness.
- **Academic & OSS Research** — Study bug lifecycle, label taxonomies, and contributor engagement patterns across large repositories like the Linux kernel or major CLIs.

### Key Features

- Accepts repository URLs or `owner/repo` shorthand, mixed freely in one run
- Filter by issue `state`: open, closed, or all
- Excludes pull requests by default (`includePullRequests: false`) — GitHub's API returns both, this Actor separates them
- Configurable `maxResults` cap per repository, or unlimited (`0`) for full issue history
- Returns full issue body text, labels, assignees, and author metadata in one call
- Structured JSON output ready for CSV, Excel, or BI tool import

### Input Parameters

| Parameter | Type | Required | Default | Description |
| --- | --- | --- | --- | --- |
| `repositories` | Array of strings | Yes | — | Repo URLs or `owner/name` (e.g. `https://github.com/cli/cli`, `torvalds/linux`) |
| `state` | String | No | `"open"` | Filter by issue state: `open`, `closed`, or `all` |
| `includePullRequests` | Boolean | No | `false` | GitHub's Issues API also returns PRs; set `true` to keep them in the results |
| `maxResults` | Integer | No | `100` | Maximum issues per repository; `0` returns all pages |

Valid input sample:

```json
{
  "repositories": [
    "https://github.com/cli/cli"
  ],
  "state": "open",
  "includePullRequests": false,
  "maxResults": 100
}
```

### Output Data Structure

Each output item represents one issue, including repository context, state and labels, author identity, comment count, and full body text.

```json
{
  "repo_full_name": "cli/cli",
  "repo_owner": "cli",
  "repo_name": "cli",
  "id": 5388523201,
  "number": 14394,
  "title": "`gh pr list` with flags fails JSON parsing",
  "state": "open",
  "state_reason": "reopened",
  "locked": false,
  "author": "yrahul3910",
  "author_type": "User",
  "labels": ["bug", "priority-3"],
  "assignees": [],
  "comments": 5,
  "is_pull_request": false,
  "draft": false,
  "body": "### Describe the bug\n\nWhen `gh pr list` is called with filters...",
  "html_url": "https://github.com/cli/cli/issues/14394",
  "created_at": "2026-09-08T15:14:56Z",
  "updated_at": "2026-09-15T03:26:56Z",
  "closed_at": "",
  "scraped_at": "2026-09-15T06:23:24.191003+00:00"
}
```

### How to use GitHub Issues Scraper

1. Configure `repositories` and optionally `state`, `includePullRequests`, and `maxResults`.
2. Click "Start" or trigger a run via the Apify API, Python, or JavaScript SDK.
3. Preview the resulting issues dataset in the Apify Console.
4. Export to JSON, CSV, or Excel, or route it into Zapier, Webhooks, or Google Drive.

### Integrations & Export Options

Results export natively to JSON, CSV, Excel, and XML, and integrate directly with n8n, Zapier, and Make for no-code automation pipelines. The dataset can also sync into database pipelines (Postgres, BigQuery, Airtable) or trigger webhook-based workflows for continuous issue monitoring and alerting.

### Custom Scrapers & Enterprise Automation Solutions

> Need a customized scraping solution, tailored workflow automation, or enterprise data extraction pipeline? Get custom development, maintenance, and setup tailored to your exact infrastructure requirements:
> 📬 **[Submit Your Custom Automation Requirements](https://mk1995.github.io/contact/)**

### Frequently Asked Questions (FAQ)

**1. Is scraping GitHub issues legal and compliant?**
Issue data on public repositories is publicly visible, and scraping it is generally acceptable, but always review GitHub's Terms of Service and applicable data protection regulations before using it commercially, especially where issue bodies may contain personal information.

**2. How much does it cost to scrape GitHub issues using this Actor?**
Cost is based on Apify compute units consumed, scaling with the number of repositories and issues fetched — typically low-cost even for repositories with thousands of open and closed issues.

**3. Do I need proxies or coding skills to run this scraper?**
No. The Actor is fully configurable through the Apify Console's input form — no proxy setup or coding knowledge required.

**4. How does this compare to the official GitHub API?**
The GitHub REST API's issues endpoint mixes pull requests into issue results and requires manual pagination plus authentication for higher rate limits. This Actor separates PRs from issues by default, automates pagination, and batches multiple repositories into a single consolidated dataset.

# Actor input Schema

## `repositories` (type: `array`):

Repo URLs or owner/name (e.g. https://github.com/cli/cli, torvalds/linux).

## `state` (type: `string`):

Filter by issue state.

## `includePullRequests` (type: `boolean`):

GitHub Issues API also returns PRs. Set true to keep them.

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

Maximum issues per repository. 0 = all pages.

## Actor input object example

```json
{
  "repositories": [
    "https://github.com/cli/cli"
  ],
  "state": "open",
  "includePullRequests": false,
  "maxResults": 100
}
```

# Actor output Schema

## `results` (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 = {
    "repositories": [
        "https://github.com/cli/cli"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("devil_port369-owner/github-issues-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "repositories": ["https://github.com/cli/cli"] }

# Run the Actor and wait for it to finish
run = client.actor("devil_port369-owner/github-issues-scraper").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 '{
  "repositories": [
    "https://github.com/cli/cli"
  ]
}' |
apify call devil_port369-owner/github-issues-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,devil_port369-owner/github-issues-scraper"
        }
    }
}
```

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/oqXgwqnAKOMWNThax/builds/CnRhSeGVAI5npWyD7/openapi.json