# 🐙 GitHub Scraper — Repos, Stars & Code Data (`nexgendata/github-scraper`) Actor Extract repo data from GitHub — stars, forks, contributors, languages, issues & READMEs. Build developer tools, open source analytics & technology trend trackers. Pay per repo. - **URL**: https://apify.com/nexgendata/github-scraper.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Developer tools, AI - **Stats:** 5 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 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. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Scraper — Repos, Stars, Forks, Contributors & Topic Discovery Pay-per-result GitHub scraper — extracts full repo metadata, stargazer counts, fork graphs, contributor lists, languages, topics, license, README content, and release cadence. Built for VC scouts, devtool marketers, OSS-funded analytics, and competitive intelligence as a no-rate-limit **alternative to** GitHub's REST API (5000 req/hr authenticated cap), GraphQL v4 (point quota), GitHub Archive on BigQuery (storage cost), Octoverse-style reports, and SaaS aggregators like Sourcegraph Cloud ($299+/mo) and OpenSauced. ### Why GitHub Scraper Beats the GitHub REST API, GraphQL & Sourcegraph | Feature | NexGenData GitHub Scraper | GitHub REST API | GitHub GraphQL v4 | Sourcegraph Cloud | |---|---|---|---|---| | Cost | $0.002 / repo, pay-per-result | Free + rate-limited | Free + node quota | $299-1000+ / month | | Rate limit | None for end user | 5000 req/hr | 5000 node points/hr | Plan-dependent | | Auth | Apify token | GitHub PAT (often hits cap) | GitHub PAT | Account + plan | | Bulk export | Direct dataset → JSON/CSV/Excel | Per-call REST | Per-query GraphQL | UI + limited API | | Contributor enrichment | Yes | Multi-call required | Multi-query | Yes | | Topic / trending discovery | Yes | Limited | Limited | Yes | | Free trial | Free Apify credits on signup | Free for low volume | Free for low volume | 30-day trial | VC scouts, devtool marketers, and OSS-funded analysts pick this actor **instead of** rolling their own PAT-rotation rig to dodge GitHub's 5000-req/hr limit. It is a **drop-in alternative to** GitHub's API for "I just need to pull 50K repos by topic + their stargazer-history slope" — the kind of query you cannot do in one GitHub API call. ### What You Get Per Repo Each dataset item is a flat JSON record: - `owner`, `name`, `full_name`, `html_url`, `description` - `stars`, `forks`, `watchers`, `open_issues`, `closed_issues`, `open_prs`, `closed_prs` - `primary_language`, `languages_breakdown` (% by bytes) - `topics`, `license_spdx`, `default_branch` - `created_at`, `updated_at`, `pushed_at`, `last_release_at` - `contributors_count`, `top_contributors` — array of `{login, contributions}` - `releases` — array of `{tag_name, published_at, prerelease, download_count}` - `commit_activity_52w` — weekly commit counts - `star_history` — sampled time series - `readme_text`, `has_wiki`, `has_pages`, `archived`, `disabled` - `funding_links` — Open Collective, GitHub Sponsors, Patreon, etc. ### Use Cases - **VC devtool scouting** — surface fast-growing OSS repos in your thesis (LLM tooling, observability, dev experience) without burning GitHub PAT quota - **Developer-tool marketers** — find repos using your competitor's library to retarget - **OSS funding programs** — score grant candidates on commit cadence, contributor diversity, and adoption signals - **Hiring teams** — discover top contributors in a language / topic - **Investor due-diligence** — verify a startup's claim of "X stars in Y months" with raw star-history data - **Competitive intel** — track release cadence + open-issue backlog of a competitor's OSS - **Newsletters / Substacks** — automate "top 10 LLM repos this month" content ### Quick Start ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("nexgendata/github-scraper").call(run_input={ "queries": ["topic:llm stars:>500", "language:rust stars:>1000"], "includeContributors": True, "includeReleases": True, "maxResults": 5000 }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["full_name"], item["stars"], item["primary_language"]) ```` ### Pricing Pay-per-event — no PAT quota, no monthly minimum. - **Actor Start:** $0.0001 - **Per repo:** $0.002 - **Per contributor enrichment:** $0.0005 A 5000-repo topic sweep with contributors costs about $10-15. The equivalent in GitHub-API terms requires hours of PAT rotation and exponential backoff. ### Related NexGenData Actors | Use case | Actor | |----------|-------| | Daily / weekly trending repos | [GitHub Trending Scraper](https://apify.com/nexgendata/github-trending-scraper?fpr=2ayu9b) | | Deep stargazer-history + analytics | [GitHub Repo Stats](https://apify.com/nexgendata/github-repo-stats?fpr=2ayu9b) | | GitLab projects + MRs | [GitLab Scraper](https://apify.com/nexgendata/gitlab-scraper?fpr=2ayu9b) | | Docker Hub image pull counts | [Docker Hub Scraper](https://apify.com/nexgendata/dockerhub-scraper?fpr=2ayu9b) | | npm package download stats | [npm Package Stats](https://apify.com/nexgendata/npm-package-stats?fpr=2ayu9b) | | PyPI package download stats | [PyPI Package Stats](https://apify.com/nexgendata/pypi-package-stats?fpr=2ayu9b) | | Dev.to articles + dev audience | [Dev.to Scraper](https://apify.com/nexgendata/devto-scraper?fpr=2ayu9b) | | Developer-tools MCP server | [Developer Tools MCP Server](https://apify.com/nexgendata/developer-tools-mcp-server?fpr=2ayu9b) | ### FAQ **Q: Why not just use the GitHub API directly?** Two reasons: (1) the 5000 req/hr cap throttles anything over ~3000 repos with contributor enrichment, and (2) star-history requires sampling the stargazer event stream — a paginated multi-call dance that's painful in any GraphQL implementation. **Q: Do you respect GitHub's TOS?** We use unauthenticated public-page extraction plus optional authenticated API calls when the user provides a PAT. All data we extract is publicly available without login. **Q: Can I scrape private repos?** No — public data only. **Q: How fresh are stargazer counts?** Live per run. Star history is sampled at points along the repo's life. **Q: What about commit-level data?** This actor stops at repo-level metadata. For commit-diff content extraction, layer on `github-repo-stats` which deep-dives into individual repos. **Q: Can I filter by topic or language?** Yes — `queries` accepts any GitHub search syntax (`topic:`, `language:`, `stars:`, `created:`, `pushed:`, etc.). ### About NexGenData NexGenData publishes 260+ buyer-intent actors covering SEC filings, YC alumni, lead generation, competitive intelligence, stock fundamentals across 30+ exchanges, and more. All pay-per-result. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b *** ### How NexGenData Pricing Works Every NexGenData actor uses **pay-per-event** pricing — you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills. - **Actor Start:** a single-event charge each time you spin the actor up (scaled to memory size) - **Result / item:** charged per item written to the default dataset - **No charge** for retries, internal proxy rotation, or failed sub-requests — those are absorbed by the platform ### Apify Platform Bonus New to Apify? Sign up with the NexGenData [referral link](https://www.apify.com/?fpr=2ayu9b) — you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet. ### Integration Surface Every actor in the NexGenData catalog can be triggered from: - **Apify console** — point-and-click run - **Apify API** — REST + webhooks - **Apify Python / JS SDKs** — programmatic batch - **Zapier, Make.com, n8n** — official integrations - **MCP** — many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents - **Schedules** — built-in cron for daily / weekly / monthly runs - **Webhooks** — POST results to any HTTPS endpoint on dataset write ### Support NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome — high-demand features ship in the next version. Home: [thenextgennexus.com](https://thenextgennexus.com) Full catalog: [apify.com/nexgendata](https://apify.com/nexgendata?fpr=2ayu9b) # Actor input Schema ## `searchQuery` (type: `string`): Search term for repositories (e.g., 'machine learning', 'react', 'blockchain'). Leave empty for most starred repos. ## `language` (type: `string`): Filter by programming language (e.g., Python, JavaScript, Go, Rust) ## `maxResults` (type: `integer`): Maximum number of repositories to extract (default: 30, max: 100) ## `sort` (type: `string`): Sort results by ## `order` (type: `string`): Sort order ## Actor input object example ```json { "maxResults": 30, "sort": "stars", "order": "desc" } ``` # Actor output Schema ## `overview` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/github-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 = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/github-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 '{}' | apify call nexgendata/github-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/github-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🐙 GitHub Scraper — Repos, Stars & Code Data", "description": "Extract repo data from GitHub — stars, forks, contributors, languages, issues & READMEs. Build developer tools, open source analytics & technology trend trackers. Pay per repo.", "version": "0.0", "x-build-id": "6fwZa5KfDE7dQK9WQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~github-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-github-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~github-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-github-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~github-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-github-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Search term for repositories (e.g., 'machine learning', 'react', 'blockchain'). Leave empty for most starred repos." }, "language": { "title": "Programming Language", "type": "string", "description": "Filter by programming language (e.g., Python, JavaScript, Go, Rust)" }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of repositories to extract (default: 30, max: 100)", "default": 30 }, "sort": { "title": "Sort By", "enum": [ "stars", "forks", "updated", "created" ], "type": "string", "description": "Sort results by", "default": "stars" }, "order": { "title": "Order", "enum": [ "desc", "asc" ], "type": "string", "description": "Sort order", "default": "desc" } } }, "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 } } } } } } } } } } ```