# GitHub Repo Scraper - Trending AI & Topic Search (`arjunannamalai/github-trending-scraper`) Actor Find trending GitHub repos by topic (mcp, llm, agents), language, date and min stars. Enriched with stars-per-day velocity. Public API, optional token. - **URL**: https://apify.com/arjunannamalai/github-trending-scraper.md - **Developed by:** [Arjun Annamalai](https://apify.com/arjunannamalai) (community) - **Categories:** Agents, Developer tools, Automation - **Stats:** 3 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. 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 Repo Scraper 🐙 — Trending AI & Topic Search Find **trending and high-signal GitHub repositories** by topic, language, date, and stars — enriched with a **stars-per-day velocity** score. Built for the AI/agent boom (`mcp`, `llm`, `ai-agents`, `rag`). Export to JSON/CSV/Excel. For **developers, VCs, dev-tool marketers, and researchers** tracking what's taking off. ### What makes it better - **Smart query builder** — combine topics + language + creation/activity date + min stars (most scrapers only take a raw query; you can still pass one). - **Velocity enrichment** — `starsPerDay` surfaces fast-risers, not just old giants. - **`daysSinceLastPush`** — filter out abandoned repos. - Optional **GitHub token** → 30 req/min instead of 10. ### Example input ```json { "topics": ["mcp", "ai-agents"], "createdAfter": "2026-04-01", "minStars": 50, "sort": "stars", "maxItems": 200 } ```` ### Example output ```json { "fullName": "owner/cool-mcp-server", "url": "https://github.com/owner/cool-mcp-server", "stars": 4200, "starsPerDay": 38.5, "language": "TypeScript", "topics": ["mcp", "ai-agents"], "daysSinceLastPush": 1 } ``` ### Use cases - Track **new MCP / agent repos** gaining stars this month. - Build a **VC deal-flow** list of fast-rising AI tools. - Monitor a **topic** for a newsletter or competitive intel. ### Run locally ```bash pip install -r requirements.txt python3 local_test.py ``` Then `apify push`. *** *Uses the public GitHub Search API. Not affiliated with GitHub.* # Actor input Schema ## `topics` (type: `array`): GitHub topics to match, e.g. 'mcp', 'llm', 'ai-agents', 'rag'. ## `language` (type: `string`): Optional programming language filter (e.g. 'python', 'typescript'). ## `createdAfter` (type: `string`): Only repos created on/after this date (great for 'new & trending'). ## `pushedAfter` (type: `string`): Only repos with activity on/after this date. ## `minStars` (type: `integer`): Only repos with at least this many stars. ## `query` (type: `string`): Optional raw GitHub search query. If set, it overrides the filters above. ## `sort` (type: `string`): How to rank the results. ## `githubToken` (type: `string`): A personal access token raises the rate limit from 10 to 30 requests/min. No scopes needed for public search. ## `maxItems` (type: `integer`): Cap on total repos (GitHub search maxes at 1000). ## Actor input object example ```json { "topics": [ "mcp" ], "sort": "stars", "maxItems": 100 } ``` # 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 = { "topics": [ "mcp" ] }; // Run the Actor and wait for it to finish const run = await client.actor("arjunannamalai/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 = { "topics": ["mcp"] } # Run the Actor and wait for it to finish run = client.actor("arjunannamalai/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 '{ "topics": [ "mcp" ] }' | apify call arjunannamalai/github-trending-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=arjunannamalai/github-trending-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Repo Scraper - Trending AI & Topic Search", "description": "Find trending GitHub repos by topic (mcp, llm, agents), language, date and min stars. Enriched with stars-per-day velocity. Public API, optional token.", "version": "0.1", "x-build-id": "OWSeWtwSYA7w4B8I7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/arjunannamalai~github-trending-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-arjunannamalai-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/arjunannamalai~github-trending-scraper/runs": { "post": { "operationId": "runs-sync-arjunannamalai-github-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/arjunannamalai~github-trending-scraper/run-sync": { "post": { "operationId": "run-sync-arjunannamalai-github-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "topics": { "title": "Topics", "type": "array", "description": "GitHub topics to match, e.g. 'mcp', 'llm', 'ai-agents', 'rag'.", "items": { "type": "string" } }, "language": { "title": "Language", "type": "string", "description": "Optional programming language filter (e.g. 'python', 'typescript')." }, "createdAfter": { "title": "Created after (YYYY-MM-DD)", "type": "string", "description": "Only repos created on/after this date (great for 'new & trending')." }, "pushedAfter": { "title": "Pushed after (YYYY-MM-DD)", "type": "string", "description": "Only repos with activity on/after this date." }, "minStars": { "title": "Minimum stars", "type": "integer", "description": "Only repos with at least this many stars." }, "query": { "title": "Raw query (advanced)", "type": "string", "description": "Optional raw GitHub search query. If set, it overrides the filters above." }, "sort": { "title": "Sort by", "enum": [ "stars", "forks", "updated", "help-wanted-issues" ], "type": "string", "description": "How to rank the results.", "default": "stars" }, "githubToken": { "title": "GitHub token (optional)", "type": "string", "description": "A personal access token raises the rate limit from 10 to 30 requests/min. No scopes needed for public search." }, "maxItems": { "title": "Max items", "minimum": 1, "type": "integer", "description": "Cap on total repos (GitHub search maxes at 1000).", "default": 100 } } }, "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 } } } } } } } } } } ```