# GitHub AI/ML Trending Scraper (`serge_esteves-ai/github-ai-trending-scraper`) Actor Scrape trending GitHub repositories filtered to AI/ML projects, with real star gains per period (today/week/month). - **URL**: https://apify.com/serge\_esteves-ai/github-ai-trending-scraper.md - **Developed by:** [serge esteves](https://apify.com/serge_esteves-ai) (community) - **Categories:** AI, Automation, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 AI/ML Trending Scraper extracts the **trending repositories from [github.com/trending](https://github.com/trending)** — the same data GitHub shows on its Trending page, including the real **star gain for the period** (today, this week, or this month). It ships with a built-in **AI / Machine Learning filter** (pre-filled keywords and GitHub topics) so you get trending AI projects out of the box — but the filter is **optional and fully customizable**: turn it off to get every trending repo, or swap the keywords/topics to track **any theme** (web scraping, DevOps, game dev, anything). Run it on the [Apify platform](https://apify.com) for scheduling, API access, proxy rotation, and integrations. ### What does GitHub AI/ML Trending Scraper do? It fetches one or more `github.com/trending/` pages, parses every repository row, and returns structured data: repository name, description, language, total stars, forks, and **stars gained in the selected period**. By default it then keeps only repositories matching a pre-filled **AI/ML** keyword/topic list — but you can edit that list to filter by any theme, or disable filtering entirely to return the full trending list. Optionally, it enriches each repo with metadata from the GitHub API (topics, license, homepage, open issues, created/pushed dates). ### Why use it? - **Track the AI/ML open-source landscape** — see which models, agents, and libraries are breaking out today, this week, or this month. - **Tech newsletters & content** — a ready-made, deduplicated list of trending AI projects. - **Investment / market research** — star velocity is an early signal of developer traction. - **Competitive intelligence** — monitor new AI tools as they gain momentum. ### How to use it 1. Open the Actor and click **Try for free / Start**. 2. Pick a **time range** (Today / This week / This month). 3. Choose the **programming languages** to scan (default: `python`, `jupyter-notebook`). 4. Leave **AI/ML repositories only** enabled and pick a **match mode** (keywords, topics, or both). 5. Click **Start** and download the results as JSON, CSV, or Excel. ### Input Configure the run in the **Input** tab. Key fields: | Field | Description | | --- | --- | | `since` | Trending period: `daily`, `weekly`, or `monthly`. | | `languages` | GitHub trending language slugs (e.g. `python`, `jupyter-notebook`, `rust`). Empty = all languages. | | `aiOnly` | Keep only AI/ML repos, detected via a built-in topic + keyword dictionary (default `true`). Set `false` to return every trending repo. | | `filterTopics` | Optional. Keep only repos having at least one of these GitHub topics (OR match). Empty = skip. | | `filterKeywords` | Optional. Keep only repos whose name/description contains one of these words (OR match, whole-word). Empty = skip. | | `includeMetadata` | Enrich each repo with GitHub API metadata. | | `maxRepos` | Max results after filtering (sorted by star gain). `0` = no limit. | | `githubToken` | Optional, secret. Raises the GitHub API rate limit from 60 to 5000 req/h for enrichment. | | `proxyConfiguration` | Proxy used to fetch trending pages. | Example input: ```json { "since": "daily", "languages": ["python", "jupyter-notebook"], "aiOnly": true, "matchMode": "both", "maxRepos": 50 } ```` #### About the optional GitHub token The token is **never stored in the Actor's code**. It is a per-run, secret input. It is only used to authenticate read-only calls to the public GitHub API so you get a higher rate limit. Without a token, enrichment still works but is limited to 60 requests/hour. ### Output Each dataset item represents one trending AI/ML repository. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. ```json { "rank": 1, "repository": "Shubhamsaboo/awesome-llm-apps", "owner": "Shubhamsaboo", "name": "awesome-llm-apps", "url": "https://github.com/Shubhamsaboo/awesome-llm-apps", "description": "100+ AI Agent & RAG apps you can actually run — clone, customize, ship.", "language": "Python", "stars": 119319, "forks": 17719, "starsInPeriod": 1006, "period": "daily", "topics": ["llm", "rag", "ai-agents"], "license": "Apache-2.0" } ``` #### Data fields | Field | Description | | --- | --- | | `rank` | Position in the filtered, star-gain-sorted list. | | `repository` | `owner/name` full repository slug. | | `url` | Repository URL. | | `description` | Repository description. | | `language` | Primary programming language. | | `starsInPeriod` | Stars gained in the selected period (today/week/month). | | `stars` | Total stars. | | `forks` | Total forks. | | `topics` | GitHub topics (only when enrichment is enabled). | | `license`, `homepage`, `openIssues`, `watchers`, `createdAt`, `pushedAt` | Extra metadata (only when enrichment is enabled). | ### Cost estimation The trending pages are lightweight HTML — a run scraping a few languages costs a tiny fraction of a compute unit. Enrichment adds one GitHub API call per repository (free, rate-limited). For most users this comfortably fits within the Apify free tier. ### Tips - Add more `languages` (e.g. `rust`, `typescript`, `c++`) to widen coverage of AI/ML projects outside Python. - Use `matchMode: "both"` for the widest AI/ML net; use `topics` for the most precise filtering. - Provide a `githubToken` if you enable enrichment across many languages, to avoid the 60 req/h limit. - Schedule the Actor daily to build a historical trend dataset. ### FAQ and support **Is scraping GitHub Trending legal?** This Actor only accesses publicly available pages and the public GitHub API. Use the data in compliance with GitHub's Terms of Service. It does not collect any personal or private data. **Why are some fields empty?** `topics` and metadata fields are only populated when enrichment is enabled (`includeMetadata`, or `matchMode` using topics). Found a bug or need a custom field? Open an issue in the **Issues** tab. # Actor input Schema ## `since` (type: `string`): Trending period, exactly like the tabs on github.com/trending. ## `languages` (type: `array`): GitHub trending language slugs to scrape (e.g. `python`, `jupyter-notebook`, `typescript`, `rust`, `c++`). Each becomes one page github.com/trending/, and GitHub returns ~25 repos per page — so listing several languages returns more candidates. Leave empty to scrape the single all-languages trending page. ## `aiOnly` (type: `boolean`): When enabled, keep only repositories related to AI, machine learning, LLMs, deep learning, agents, etc. Classification uses a built-in dictionary of GitHub topic tags AND name/description keywords (a repo matches if either hits). Turn off to return every trending repo. To filter by your own criteria instead, use the two fields below. ## `filterTopics` (type: `array`): Keep only repos that have at least one of these GitHub topic tags (OR match). Examples: `mcp`, `rag`, `computer-vision`, `web-scraping`, `devops`, `game-engine`. Requires topic data, so enabling this fetches topics from the GitHub API. Leave empty to skip topic filtering. Combined with the other filters using AND. ## `filterKeywords` (type: `array`): Keep only repos whose NAME or DESCRIPTION contains at least one of these words (OR match, whole-word, case-insensitive). Examples: `langchain`, `diffusion`, `agent`, `scraper`, `kubernetes`. Leave empty to skip keyword filtering. Combined with the other filters using AND. ## `includeMetadata` (type: `boolean`): Fetch extra fields per repo from the GitHub API (topics, license, homepage, open issues, created/pushed dates, watchers). Automatically enabled when the AI/ML filter or topic filtering is used. ## `maxRepos` (type: `integer`): Maximum number of repositories to output after filtering (0 = no limit). Results are sorted by star gain in the selected period, descending. ## `githubToken` (type: `string`): Optional personal access token (read-only / public scope is enough). Only used to raise the GitHub API rate limit from 60 to 5000 requests/hour for metadata and topic enrichment. Never stored in the code — provided per run and treated as a secret. ## `proxyConfiguration` (type: `object`): Proxy used to fetch the github.com/trending pages. ## Actor input object example ```json { "since": "daily", "languages": [ "python", "jupyter-notebook" ], "aiOnly": true, "filterTopics": [], "filterKeywords": [], "includeMetadata": false, "maxRepos": 100, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `repositories` (type: `string`): No description ## `datasetOverview` (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": [ "python", "jupyter-notebook" ], "filterTopics": [], "filterKeywords": [] }; // Run the Actor and wait for it to finish const run = await client.actor("serge_esteves-ai/github-ai-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": [ "python", "jupyter-notebook", ], "filterTopics": [], "filterKeywords": [], } # Run the Actor and wait for it to finish run = client.actor("serge_esteves-ai/github-ai-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": [ "python", "jupyter-notebook" ], "filterTopics": [], "filterKeywords": [] }' | apify call serge_esteves-ai/github-ai-trending-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=serge_esteves-ai/github-ai-trending-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub AI/ML Trending Scraper", "description": "Scrape trending GitHub repositories filtered to AI/ML projects, with real star gains per period (today/week/month).", "version": "0.1", "x-build-id": "2hvaEPsD0uy7FVf8O" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/serge_esteves-ai~github-ai-trending-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-serge_esteves-ai-github-ai-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/serge_esteves-ai~github-ai-trending-scraper/runs": { "post": { "operationId": "runs-sync-serge_esteves-ai-github-ai-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/serge_esteves-ai~github-ai-trending-scraper/run-sync": { "post": { "operationId": "run-sync-serge_esteves-ai-github-ai-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "since": { "title": "Time range", "enum": [ "daily", "weekly", "monthly" ], "type": "string", "description": "Trending period, exactly like the tabs on github.com/trending.", "default": "daily" }, "languages": { "title": "Programming languages", "type": "array", "description": "GitHub trending language slugs to scrape (e.g. `python`, `jupyter-notebook`, `typescript`, `rust`, `c++`). Each becomes one page github.com/trending/, and GitHub returns ~25 repos per page — so listing several languages returns more candidates. Leave empty to scrape the single all-languages trending page.", "default": [ "python", "jupyter-notebook" ], "items": { "type": "string" } }, "aiOnly": { "title": "AI/ML repositories only", "type": "boolean", "description": "When enabled, keep only repositories related to AI, machine learning, LLMs, deep learning, agents, etc. Classification uses a built-in dictionary of GitHub topic tags AND name/description keywords (a repo matches if either hits). Turn off to return every trending repo. To filter by your own criteria instead, use the two fields below.", "default": true }, "filterTopics": { "title": "Filter by topics", "type": "array", "description": "Keep only repos that have at least one of these GitHub topic tags (OR match). Examples: `mcp`, `rag`, `computer-vision`, `web-scraping`, `devops`, `game-engine`. Requires topic data, so enabling this fetches topics from the GitHub API. Leave empty to skip topic filtering. Combined with the other filters using AND.", "default": [], "items": { "type": "string" } }, "filterKeywords": { "title": "Filter by keywords", "type": "array", "description": "Keep only repos whose NAME or DESCRIPTION contains at least one of these words (OR match, whole-word, case-insensitive). Examples: `langchain`, `diffusion`, `agent`, `scraper`, `kubernetes`. Leave empty to skip keyword filtering. Combined with the other filters using AND.", "default": [], "items": { "type": "string" } }, "includeMetadata": { "title": "Enrich with GitHub API metadata", "type": "boolean", "description": "Fetch extra fields per repo from the GitHub API (topics, license, homepage, open issues, created/pushed dates, watchers). Automatically enabled when the AI/ML filter or topic filtering is used.", "default": false }, "maxRepos": { "title": "Max repositories", "minimum": 0, "type": "integer", "description": "Maximum number of repositories to output after filtering (0 = no limit). Results are sorted by star gain in the selected period, descending.", "default": 100 }, "githubToken": { "title": "GitHub token (optional)", "type": "string", "description": "Optional personal access token (read-only / public scope is enough). Only used to raise the GitHub API rate limit from 60 to 5000 requests/hour for metadata and topic enrichment. Never stored in the code — provided per run and treated as a secret." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy used to fetch the github.com/trending pages.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```