# GitHub Trending Scraper (`fetch_cat/github-trending-scraper`) Actor Scrape GitHub Trending repositories by language and time window for developer research, newsletters, and market intelligence. - **URL**: https://apify.com/fetch\_cat/github-trending-scraper.md - **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community) - **Categories:** Developer tools, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.03 / 1,000 trending repository saveds 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/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 Trending Scraper Track public GitHub Trending repositories by language and time window. The actor saves ranked repositories, descriptions, languages, stars, forks, stars gained, contributor avatars, and optional README text so you can monitor fast-moving developer ecosystems without copying pages by hand. ### At a glance - **Best for:** open-source trend monitoring, developer relations, newsletter research, market intelligence, and technical ecosystem tracking. - **Inputs:** GitHub languages, trending time window, maximum repositories, optional README enrichment, and proxy settings. - **Outputs:** one row per trending repository with rank, owner, repo, URL, description, language, stars, forks, stars gained, contributors, source URL, and timestamp. - **Exports:** download CSV, JSON, Excel, XML, RSS, or use the Apify Dataset API. - **Cost:** `$0.005` per run plus the `item` event for each saved repository row. ### Ready-to-run examples Use these saved Store examples as starting points. Open any example to prefill the Actor input, then adjust URLs, keywords, limits, or filters for your own run. - **[Create a monthly open-source trend dataset](https://apify.com/fetch_cat/github-trending-scraper/examples/monthly-open-source-trend-dataset)** - **[Track trending repositories across multiple languages](https://apify.com/fetch_cat/github-trending-scraper/examples/multi-language-dev-tool-trends)** - **[Scrape weekly Go trending repositories](https://apify.com/fetch_cat/github-trending-scraper/examples/go-trending-repositories-weekly)** - **[Scrape monthly Rust trending repositories](https://apify.com/fetch_cat/github-trending-scraper/examples/rust-trending-repositories-monthly)** - **[Scrape trending AI repositories with README text](https://apify.com/fetch_cat/github-trending-scraper/examples/ai-open-source-trending-readmes)** - **[Scrape JavaScript and TypeScript trending repositories](https://apify.com/fetch_cat/github-trending-scraper/examples/javascript-typescript-trending-repos)** - **[View all ready-to-run examples](https://apify.com/fetch_cat/github-trending-scraper/examples)** (8 examples) ### What can it do? - **Scrape overall GitHub Trending:** collect the public overall Trending page for daily, weekly, or monthly windows. - **Scrape language-specific trends:** track JavaScript, Python, TypeScript, Go, Rust, and other GitHub language pages. - **Export repository metrics:** save repository names, owners, URLs, descriptions, languages, stars, forks, and stars gained. - **Collect contributor hints:** save public contributor avatars and profile links shown on Trending cards. - **Enrich with README text:** optionally fetch public README text for smaller research or classification runs. - **Build a repeatable trend monitor:** schedule the same input and compare saved datasets across runs. ### Who is it for? This actor is useful for several teams: - **Developer-relations teams:** track projects that are suddenly gaining attention. - **Content teams:** build newsletters and research queues around open-source tools. - **VC and market-intelligence teams:** discover emerging developer infrastructure and ecosystems. - **Recruiting teams:** watch active projects and technical communities. - **Product teams:** monitor competing frameworks, SDKs, and AI tools. - **Data teams:** build repeatable GitHub trend dashboards. ### Why use it? GitHub Trending is easy to view once, but hard to monitor reliably over time. This actor turns the page into structured rows that can be exported, scheduled, and connected to your workflows. Use it when you need: - Repeatable snapshots of trending repositories - Language-specific open-source discovery - A clean dataset instead of screenshots or pasted HTML - Automation that can run daily, weekly, or monthly - Fields that are ready for spreadsheet, BI, CRM, or alerting workflows ### Output fields | Field | Description | | --- | --- | | `rank` | Repository rank on the requested Trending page | | `owner` | GitHub owner or organization | | `repo` | Repository name | | `fullName` | `owner/repo` value | | `repoUrl` | Public GitHub repository URL | | `repositoryDescription` | Repository description shown on Trending | | `language` | Primary language shown on Trending | | `stars` | Total stargazers count | | `forks` | Total forks count | | `starsGained` | Stars gained in the selected time window | | `builtBy` | Public usernames, profile URLs, and avatar URLs shown by GitHub | | `since` | Requested time window | | `trendingLanguage` | Requested language or `overall` | | `trendingUrl` | Source Trending URL | | `scrapedAt` | Timestamp when the row was saved | | `readmeUrl` | README URL when enrichment is enabled | | `readmeText` | README text when enrichment is enabled | | `readmeTruncated` | Whether README text was shortened | ### Pricing The actor uses pay-per-event pricing. You pay a small start fee plus a per-repository charge for saved dataset rows. | Charge event | Exact price | Charged when | | --- | ---: | --- | | `apify-actor-start` | `$0.005` | Once when the run starts. | | `item` | `$0.0000538` at BRONZE tier | For each repository row saved to the dataset. | At the BRONZE tier, the saved-record charge is about `$0.0538` per 1,000 saved repository rows, plus the run start fee. Only rows saved to the dataset are charged as `item` events. The final amount is shown in the Apify run billing details. ### Quick start 1. Open the actor on Apify. 2. Choose one or more languages, or leave the language list empty for overall Trending. 3. Select `daily`, `weekly`, or `monthly`. 4. Set `maxItems`. 5. Keep `includeReadme` disabled for the fastest first run. 6. Start the actor. 7. Download the dataset as JSON, CSV, Excel, or via API. ### Input configuration | Setting | JSON key | What it does | | --- | --- | --- | | GitHub languages | `languages` | Array of GitHub language names or slugs such as `javascript`, `python`, `typescript`, `go`, or `rust`. Leave empty for overall Trending. | | Time window | `since` | Choose `daily`, `weekly`, or `monthly`. | | Maximum repositories | `maxItems` | Maximum repositories to save across all requested pages. Use a small number for quick tests. | | Include README text | `includeReadme` | Fetches public README text from common README paths. This adds extra requests, so keep it off unless you need text enrichment. | | Proxy configuration | `proxyConfiguration` | Optional proxy settings. Most runs should work without proxy because GitHub Trending is public. | ### Example input ```json { "languages": ["javascript", "python", "typescript"], "since": "daily", "maxItems": 30, "includeReadme": false, "proxyConfiguration": { "useApifyProxy": false } } ```` ### Example output item ```json { "rank": 1, "owner": "sveltejs", "repo": "svelte", "fullName": "sveltejs/svelte", "repoUrl": "https://github.com/sveltejs/svelte", "repositoryDescription": "web development for the rest of us", "language": "JavaScript", "stars": 87592, "forks": 4960, "starsGained": 29, "builtBy": [ { "username": "Rich-Harris", "profileUrl": "https://github.com/Rich-Harris", "avatarUrl": "https://avatars.githubusercontent.com/u/1162160?s=40&v=4" } ], "since": "daily", "trendingLanguage": "javascript", "trendingUrl": "https://github.com/trending/javascript?since=daily", "scrapedAt": "2026-06-30T08:00:00.000Z" } ``` ### Tips for best results - Start with one or two languages and `maxItems` around 20. - Schedule daily runs if you want a trend history. - Use weekly or monthly windows for less noisy research. - Enable README enrichment only for smaller runs or when text analysis is required. - Store each scheduled run's dataset if you want time-series comparisons. ### Common workflows - **Daily developer-news monitoring:** run the Actor every morning for `javascript`, `python`, and `typescript`, then send new repositories to a Slack channel or newsletter draft. - **VC and startup discovery:** run weekly Trending snapshots for AI, data, security, and infrastructure languages to review fast-growing repositories. - **Competitive intelligence:** monitor languages and frameworks related to your product category, then export `starsGained`, descriptions, and README text for classification. - **Recruiting research:** review `builtBy` users and active repositories in specific technology communities as a starting point for public GitHub profile research. ### Integrations You can connect the dataset to: - Google Sheets for editorial calendars - Slack alerts through Apify integrations - Airtable or Notion for research queues - BigQuery, Snowflake, or S3 for long-term trend storage - Zapier or Make for no-code workflows - Custom dashboards through the Apify API ### API usage with Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('fetch_cat/github-trending-scraper').call({ languages: ['javascript', 'python'], since: 'daily', maxItems: 20, includeReadme: false, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### API usage with Python ```python from apify_client import ApifyClient import os client = ApifyClient(os.environ['APIFY_TOKEN']) run = client.actor('fetch_cat/github-trending-scraper').call(run_input={ 'languages': ['javascript', 'python'], 'since': 'daily', 'maxItems': 20, 'includeReadme': False, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items) ``` ### API usage with cURL ```bash curl -X POST "https://api.apify.com/v2/acts/fetch_cat~github-trending-scraper/runs?token=$APIFY_TOKEN" \ -H 'Content-Type: application/json' \ -d '{ "languages": ["javascript", "python"], "since": "daily", "maxItems": 20, "includeReadme": false }' ``` ### MCP and AI agents You can use this actor from AI tools through the official Apify MCP server. MCP endpoint: ```text https://mcp.apify.com?tools=fetch_cat/github-trending-scraper ``` Claude Code setup: ```bash claude mcp add apify-github-trending --url "https://mcp.apify.com?tools=fetch_cat/github-trending-scraper" ``` Claude Desktop JSON configuration: ```json { "mcpServers": { "apify-github-trending": { "url": "https://mcp.apify.com?tools=fetch_cat/github-trending-scraper" } } } ``` The default Apify MCP server can search and run Actors. The focused URL exposes only this Actor to clients that support tool-scoped MCP connections. Example prompts for MCP usage: Developer tooling trend summary: ```text Use fetch_cat/github-trending-scraper to get today's top JavaScript and Python GitHub Trending repositories. Summarize the top 10 by stars gained and identify projects that look relevant to AI developer tooling. ``` Backend infrastructure review: ```text Run the GitHub Trending Scraper for rust and go weekly trends, then create a table with repository, description, stars gained, and why each project may matter to backend infrastructure teams. ``` Weekly newsletter draft: ```text Every Monday, run fetch_cat/github-trending-scraper for go, rust, and python weekly trends, then draft a short engineering newsletter with repository links and stars gained. ``` ### Scheduling For monitoring, schedule the actor to run daily or weekly. Keep the same input each time, then compare datasets across runs. Good schedules include: - Daily at 08:00 for newsletters - Weekly on Monday for market research - Monthly for broad ecosystem reports ### Limitations - The actor extracts data visible on public GitHub Trending pages. - GitHub may change page layout, which can require parser updates. - Trending pages usually contain a limited number of repositories per language/window. - README enrichment may not find every repository README because branch names and file names vary. - The actor does not access private repositories or account-only data. ### FAQ #### Why did I get fewer items than requested? GitHub Trending pages have a finite number of visible repositories. If the source page has fewer repositories than your `maxItems`, the actor saves all available repositories. #### Why is README text missing? README enrichment checks common public README locations. Some repositories use different default branches, different file names, generated documentation, or no README. #### Should I enable proxy? Usually no. GitHub Trending is public. Enable proxy only if your run environment requires it or you repeatedly see network-level errors. ### Data freshness GitHub Trending changes over time. The actor saves the state visible during the run and includes `scrapedAt` so you can compare snapshots. ### Legality This actor collects public information from GitHub Trending pages. Use the data responsibly, respect GitHub's terms, avoid excessive scheduling, and do not use the output for spam, harassment, or invasive profiling. ### Related actors - [GitHub Repositories Search Scraper](https://apify.com/fetch_cat/github-repositories-search-scraper) - search GitHub repositories by keyword, language, stars, and update date. - [Hacker News Search Scraper](https://apify.com/fetch_cat/hacker-news-search-scraper) - monitor developer and startup discussions. - [Stack Exchange Questions Scraper](https://apify.com/fetch_cat/stack-exchange-questions-scraper) - export technical question datasets. - [Product Hunt Scraper](https://apify.com/fetch_cat/product-hunt-scraper) - track startup launches and product discovery. ### Changelog - 2026-07-04 - Feature: Launched GitHub Trending Scraper on Apify Store (APIA-1222) - This actor is now publicly available at https://apify.com/fetch\_cat/github-trending-scraper. #### 0.1 - Initial release with language-specific GitHub Trending scraping, daily/weekly/monthly windows, repository metadata extraction, contributor avatar extraction, optional README enrichment, pricing events, and dataset schema. ### Support If a run fails, returns no data, or a field looks wrong, open an issue from the Actor page. Please include the Apify run ID or run URL, input JSON, one example public URL, query, or input item, what you expected, and what the dataset returned. Small reproducible inputs make parsing or site-layout issues much faster to fix. # Actor input Schema ## `languages` (type: `array`): GitHub language slugs or names to scrape, for example `javascript`, `python`, or `TypeScript`. Leave empty to scrape the overall Trending page. ## `since` (type: `string`): GitHub Trending time window to scrape. ## `maxItems` (type: `integer`): Maximum number of repositories to save across all requested Trending pages. ## `includeReadme` (type: `boolean`): Fetch README text from common public README locations. This adds extra requests and is best for smaller runs. ## `proxyConfiguration` (type: `object`): Optional Apify Proxy settings. Leave disabled for normal GitHub Trending scraping. ## Actor input object example ```json { "languages": [ "javascript", "python" ], "since": "daily", "maxItems": 20, "includeReadme": false, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "languages": [ "javascript", "python" ] }; // Run the Actor and wait for it to finish const run = await client.actor("fetch_cat/github-trending-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 = { "languages": [ "javascript", "python", ] } # Run the Actor and wait for it to finish run = client.actor("fetch_cat/github-trending-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 '{ "languages": [ "javascript", "python" ] }' | apify call fetch_cat/github-trending-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetch_cat/github-trending-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Trending Scraper", "description": "Scrape GitHub Trending repositories by language and time window for developer research, newsletters, and market intelligence.", "version": "0.1", "x-build-id": "nWsihPcoo4of7Yzbv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetch_cat~github-trending-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetch_cat-github-trending-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/fetch_cat~github-trending-scraper/runs": { "post": { "operationId": "runs-sync-fetch_cat-github-trending-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/fetch_cat~github-trending-scraper/run-sync": { "post": { "operationId": "run-sync-fetch_cat-github-trending-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", "required": [ "since", "maxItems" ], "properties": { "languages": { "title": "Languages", "type": "array", "description": "GitHub language slugs or names to scrape, for example `javascript`, `python`, or `TypeScript`. Leave empty to scrape the overall Trending page.", "items": { "type": "string" } }, "since": { "title": "Time window", "enum": [ "daily", "weekly", "monthly" ], "type": "string", "description": "GitHub Trending time window to scrape.", "default": "daily" }, "maxItems": { "title": "Maximum repositories", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of repositories to save across all requested Trending pages.", "default": 20 }, "includeReadme": { "title": "Include README text", "type": "boolean", "description": "Fetch README text from common public README locations. This adds extra requests and is best for smaller runs.", "default": false }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify Proxy settings. Leave disabled for normal GitHub Trending scraping.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```