GitHub Scraper — Repos, Issues, PRs & Code
Pricing
Pay per event + usage
GitHub Scraper — Repos, Issues, PRs & Code
Scrape GitHub deeply — repos, issues, PRs, code search, contributors, releases, READMEs, commits, users, trending. 11 modes in one actor for AI coding agents (Claude Code, Cursor, Copilot). Optional PAT for 5K req/hr. MCP-ready, flat JSON output.
Pricing
Pay per event + usage
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0.0
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Developer
Khadin Akbar
Maintained by CommunityActor stats
0
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23
Total users
9
Monthly active users
14 days ago
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GitHub Deep Scraper — Repos, Issues, PRs, Code Search, Commits
GitHub Deep Scraper is an Apify Actor for public GitHub data. It accepts one GitHub surface per run, such as a repository, search query, user login, or trending filter, and returns one flat record per result. Each record includes mode, type, url, and scrapedAt, plus mode-specific GitHub fields that support repo analysis, issue review, PR inspection, code search, contributor lookup, release tracking, README retrieval, commit history review, user profiling, and trending exploration.
Best fit and connected workflows
This Actor fits workflows that need one GitHub scraping tool with multiple routes:
- Repository research: use
repowhen a workflow starts from one public repository and needs a full metadata snapshot. - Issue and PR review: use
issuesorprswhen a workflow starts from a repo and needs lists, labels, comments, reviews, or review threads. - Code discovery: use
code-searchwhen a workflow starts from a text query and needs code matches across GitHub. - Contributor and release analysis: use
contributorsorreleaseswhen the workflow needs contributor profiles or release history from a repo. - Documentation extraction: use
readmewhen the workflow needs the repository README as markdown and rendered text. - Commit inspection: use
commitswhen the workflow needs commit history, and optionally file diffs. - Profile review: use
userwhen the workflow starts from a GitHub login and needs the profile plus repositories. - Trend scanning: use
trendingwhen the workflow needs trending repositories by language and timeframe.
Practical scenario
A developer advocate named Mina starts with apify/actors-mcp-server and wants to prepare a short update for her team. She runs the Actor in prs mode with state: "closed" and includeReviews: true. The returned dataset record includes the PR url, type: "pr", and scrapedAt, plus PR-specific fields for review state and review comments. Mina uses the review state and PR URL to pick one merged change for a deeper read, then shares the PR link in her team note.
Input fields
| Field | Type | Used in | Description |
|---|---|---|---|
mode | string | all modes | Selects one GitHub surface to scrape. One mode per run. |
repo | string | repo, issues, prs, contributors, releases, readme, commits | GitHub repository in owner/name format, or a full GitHub repo URL. |
query | string | repo-search, code-search | GitHub search query with qualifiers such as language:, stars:, org:, path:, and extension:. |
user | string | user | GitHub user or organization login. |
language | string | trending | Language filter for trending mode. |
timeframe | string | trending | Trending window: daily, weekly, or monthly. |
state | string | issues, prs | Issue or PR state filter: open, closed, or all. |
since | string | issues, prs, commits | ISO 8601 date for returning items updated or created at or after the given point. |
maxResults | integer | all modes | Maximum number of records to return. |
includeComments | boolean | issues, prs | Includes comments for each issue or PR. |
includeReviews | boolean | prs | Includes reviews and review comments for each PR. |
includeFiles | boolean | commits | Includes file diffs for each commit. |
Focused JSON input example
{"mode": "prs","repo": "vercel/next.js","state": "closed","includeReviews": true,"since": "2026-01-01","maxResults": 25}
Output fields
The dataset returns one record per result.
| Field | Type | Description |
|---|---|---|
mode | string | Which scraping mode produced the record. |
type | string | Record type such as repo, issue, pr, code-match, contributor, release, readme, commit, user, or trending-repo. |
url | string or null | Canonical GitHub URL for the entity. |
scrapedAt | string | ISO 8601 UTC timestamp for when the record was fetched. |
Illustrative JSON record
{"mode": "repo","type": "repo","url": "https://github.com/facebook/react","scrapedAt": "2026-05-28T18:14:32Z"}
How it works
This Actor uses GitHub's public REST API and GraphQL API surfaces for the selected mode, plus the public GitHub trending page for trending mode. The input schema defines 11 modes: repo, repo-search, issues, prs, code-search, contributors, releases, readme, commits, user, and trending. Repository-based modes normalize owner/name input, and full repository URLs are accepted for the repo field. The output dataset stays flat so downstream tools and agents can read it easily. The output contract also includes a GitHub rate-limit record in key-value storage, plus summary records for the run outcome.
Pricing
This Actor uses Apify Pay per event plus standard Apify platform usage. Open the live Pricing tab in Apify Console for the current event definitions and platform usage details before planning larger runs.
Charged events include:
apify-actor-startfor the run startresultfor simple returned recordsdeep-resultfor heavier returned records
For example, a run that returns twenty simple results is billed for one actor start event plus twenty result events, alongside Apify platform usage for the run.
Use with AI agents (MCP)
This Actor is Apify MCP-ready and usable through Apify MCP as khadinakbar/github-deep-scraper. It is a tool for retrieving structured GitHub data by mode, so an agent can request exactly the surface it needs and then read the dataset rows returned by the run.
Tool description: fetch public GitHub records for a chosen mode, then read the resulting dataset items and supporting run records such as rate-limit state.
Fetch the closed pull requests for
vercel/next.jssince the start of the year, include reviews, and return the dataset items with their GitHub URLs and scrape timestamps.
When interpreting results, treat each dataset row as one GitHub entity or search result. The shared fields identify the source mode, record type, canonical URL, and fetch time. For broader runs, use maxResults to bound how many rows the agent receives. For heavier modes and options, such as code search, PR reviews, PR comments, and commit file diffs, the deep-result event rate applies. The rate-limit record in key-value storage can help agents confirm whether a GitHub token is being applied and how many requests remain.
Apify API example
import { ApifyClient } from "apify-client";const client = new ApifyClient({token: process.env.APIFY_TOKEN,});const run = await client.actor("khadinakbar/github-deep-scraper").call({mode: "repo",repo: "facebook/react",maxResults: 1,});const { items } = await client.dataset(run.defaultDatasetId).listItems();console.log(items);
Best results and outcome guidance
Use repo when the workflow starts from one repository and needs a broad snapshot. Use repo-search when the workflow starts from a topic, stack, or qualifier query. Use issues and prs when the workflow needs discussion context, labels, reviews, or thread comments. Use commits when the workflow needs change history, and enable file diffs when reasoning about touched files matters. Use trending when the workflow needs a current list of popular repositories by language and timeframe. Set maxResults to the smallest number that covers the task so the run stays focused.
Continue the workflow
- Then use Google Play Store All-in-One Scraper — Apps, Reviews, Charts to extend GitHub Deep Scraper — Repos, Issues, PRs, Code Search, Commits with a neighboring software ecosystem research source when the brief calls for Google Play data.
- Then use App Store Reviews Scraper - iOS & macOS Ratings to extend GitHub Deep Scraper — Repos, Issues, PRs, Code Search, Commits with a neighboring software ecosystem research source when the brief calls for App Store data.
Design note
I found that the dataset contract is intentionally flat: every record includes mode, type, url, and scrapedAt, while the rest of the fields vary by mode.
FAQ
Which GitHub surface should I use for a full repository snapshot?
Use repo for one repository's full metadata.
Which mode is suited to finding repositories by topic or qualifier?
Use repo-search and pass a GitHub search query in the query field.
Which mode should I use for issue threads or PR conversations?
Use issues or prs, and turn on includeComments when you want thread context.
How do I inspect code across GitHub?
Use code-search with a search query. The live contract marks this mode as requiring the GITHUB_TOKEN environment variable.
How do I get a repository README?
Use readme with the repository name in owner/name format.
How do I get commit history with file diffs?
Use commits and set includeFiles: true when file-level reasoning matters.
How do I get trending repositories for a language?
Use trending with language and timeframe.
Responsible use
Use this Actor for public GitHub data and keep your usage aligned with GitHub's terms and applicable data-protection rules. Review the live Pricing tab before larger runs, especially when using result-heavy modes or options that add comments, reviews, or file diffs.