# GitHub Repository Stats Scraper (`neuton/github-repository-stats-scraper`) Actor Extract public GitHub repository metadata, stars, forks, issues, topics, license, owner details, and recent release data by repo URL, owner/name, user, or search query. - **URL**: https://apify.com/neuton/github-repository-stats-scraper.md - **Developed by:** [Ashwin Prasad](https://apify.com/neuton) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Repository Stats Scraper Extract clean GitHub repository intelligence for market maps, developer tooling research, open-source monitoring, lead qualification, investment research, and AI-agent workflows. This public actor accepts repository URLs, `owner/repo` slugs, GitHub users or organizations, and GitHub search queries, then returns structured repository rows that are ready for spreadsheets, CRMs, dashboards, and enrichment pipelines. ### What You Can Extract - Repository name, URL, description, topics, language, license, owner, and source mode - Stars, forks, watchers, open issues, archived/private/fork flags, and visibility context - Owner profile basics and repository metadata useful for developer-tool lead scoring - Latest release metadata when available - One row per repository so mixed inputs can be traced back to their source query ### Common Use Cases - Track open-source competitors, SDKs, AI tools, crypto projects, infrastructure projects, and developer platforms - Build market maps from GitHub search queries, repository topics, and language filters - Enrich developer-tool lead lists with stars, forks, language, license, issues, topics, and release activity - Monitor repository traction before outreach, partnership, acquisition, or investment research - Feed GitHub repository rows into dashboards, CRM systems, product-research workflows, and AI agents ### SEO Keywords GitHub repository scraper, GitHub repo stats API, GitHub stars scraper, GitHub repository search export, open source intelligence scraper, GitHub topics scraper, developer tools market map, GitHub lead enrichment. ### Example Input ```json { "repositories": ["openai/openai-python", "apify/crawlee-python"], "owners": ["vercel"], "searchQueries": ["topic:ai stars:>1000 language:Python"], "maxResultsPerSearch": 25, "includeLatestRelease": true } ```` ### Output Rows include repository name, owner, URL, description, topics, language, license, stars, forks, watchers, open issues, archived/fork flags, owner profile fields, latest release metadata, input source, and scrape timestamp. Export as JSON, CSV, Excel, or consume from the Apify API. ### Pricing Recommended monetization: pay per dataset item. Launch around $0.002 per repository row for bulk repository research, then raise only after repeat usage appears. ### Responsible Use This actor extracts public GitHub repository metadata. Use it for research, enrichment, monitoring, and discovery. Respect GitHub terms and rate limits, and avoid spam outreach, repository manipulation, or misleading claims based only on star counts. # Actor input Schema ## `repositories` (type: `array`): Repository slugs or URLs, e.g. openai/openai-python or https://github.com/openai/openai-python ## `users` (type: `array`): GitHub users/orgs to list repositories for. ## `searchQueries` (type: `array`): GitHub repository search queries, e.g. topic:llm language:python stars:>1000 ## `maxResults` (type: `integer`): Max results per user/query ## `includeLatestRelease` (type: `boolean`): Include latest release ## Actor input object example ```json { "maxResults": 50, "includeLatestRelease": true } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("neuton/github-repository-stats-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("neuton/github-repository-stats-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 neuton/github-repository-stats-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=neuton/github-repository-stats-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Repository Stats Scraper", "description": "Extract public GitHub repository metadata, stars, forks, issues, topics, license, owner details, and recent release data by repo URL, owner/name, user, or search query.", "version": "1.0", "x-build-id": "E7Hmd0zSJw16gbXTT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/neuton~github-repository-stats-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-neuton-github-repository-stats-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/neuton~github-repository-stats-scraper/runs": { "post": { "operationId": "runs-sync-neuton-github-repository-stats-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/neuton~github-repository-stats-scraper/run-sync": { "post": { "operationId": "run-sync-neuton-github-repository-stats-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "repositories": { "title": "Repositories", "type": "array", "description": "Repository slugs or URLs, e.g. openai/openai-python or https://github.com/openai/openai-python", "items": { "type": "string" } }, "users": { "title": "Users or organizations", "type": "array", "description": "GitHub users/orgs to list repositories for.", "items": { "type": "string" } }, "searchQueries": { "title": "Search queries", "type": "array", "description": "GitHub repository search queries, e.g. topic:llm language:python stars:>1000", "items": { "type": "string" } }, "maxResults": { "title": "Max results per user/query", "minimum": 1, "maximum": 100, "type": "integer", "description": "Max results per user/query", "default": 50 }, "includeLatestRelease": { "title": "Include latest release", "type": "boolean", "description": "Include latest release", "default": 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 } } } } } } } } } } ```