# NYT Articles Scraper | New York Times Headlines (`parseforge/nyt-articles-scraper`) Actor Extract New York Times articles with headline, byline, date, section, abstract, and full content. Filter by section, keyword, or date range. Ideal for media analysts, NLP datasets, sentiment research, and competitive content monitoring across US news. - **URL**: https://apify.com/parseforge/nyt-articles-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** News, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $19.00 / 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. 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿ—ž๏ธ New York Times Articles Scraper > ๐Ÿš€ **Export The New York Times articles in seconds.** Pull the latest headlines, summaries, authors, images, and publish dates straight into CSV, Excel, JSON, or XML. > ๐Ÿ•’ **Last updated:** 2026-05-25 ยท **๐Ÿ“Š 10 fields** per record ยท **top headlines from the NYT homepage feed** ยท **public The New York Times feed** The New York Times is one of the most influential daily newspapers in the world, with reporting on politics, business, tech, culture, science, and global affairs. This Actor reads the public The New York Times feed and turns each story into a clean tabular record. No login, no API key, no rate-limit headaches. Schedule it daily, hourly, or on demand and pipe the output anywhere Apify integrates. | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | Data journalists, media analysts, NLP researchers, brand monitors, newsroom engineers | Build daily news digests, populate research databases, run brand and topic monitoring, train summarization or classification models | ### ๐Ÿ“‹ What the New York Times Articles Scraper does - Pulls the latest articles from the public The New York Times feed - Returns title, URL, author, image, summary, categories, and publish date - Exports clean tabular data to CSV, Excel, JSON, or XML - Runs on demand or on a schedule - No account, token, or login required > ๐Ÿ’ก **Why it matters:** Newsroom monitoring, media datasets, and content workflows need machine-readable headlines. This Actor delivers them in seconds. ### ๐ŸŽฌ Full Demo (_๐Ÿšง Coming soon_) ### โš™๏ธ Input
FieldTypeRequiredDescription
maxItemsintegerNoMax records to return. Free plan capped at 10.
```json { "maxItems": 10 } ```` ```json { "maxItems": 100 } ``` > โš ๏ธ **Good to Know:** The public RSS feed surfaces top headlines from the NYT homepage. Paywalled story bodies remain on nytimes.com. ### ๐Ÿ“Š Output | Field | Type | Description | |---|---|---| | ๐Ÿ–ผ `imageUrl` | string | Lead image URL (when published) | | ๐Ÿ“Œ `title` | string | Article title | | ๐Ÿ”— `url` | string | Canonical article URL | | โœ๏ธ `author` | string | Byline (when published) | | ๐Ÿท๏ธ `categories` | array | Topic tags (when published) | | ๐Ÿ“… `publishedAt` | string | ISO publish timestamp | | ๐Ÿ“ `summary` | string | Short summary or dek | | ๐Ÿ“ฐ `source` | string | "The New York Times" | | ๐Ÿ•’ `scrapedAt` | string | Run timestamp | | โŒ `error` | string | Null on success | Sample record: ```json { "imageUrl": "https://static.newyorktimesarticles.example/lead.jpg", "title": "Markets close higher as investors weigh policy outlook", "url": "https://example.com/article/markets-close-higher", "author": "Staff Reporter", "categories": ["Business", "Markets"], "publishedAt": "2026-05-25T13:42:11.000Z", "summary": "Equity benchmarks edged up on Friday as traders digested fresh economic data.", "source": "The New York Times", "scrapedAt": "2026-05-25T17:46:02.873Z", "error": null } ``` ### โœจ Why choose this Actor | ๐Ÿ”ฅ Reason | Why it matters | |---|---| | ๐Ÿ†“ No account or token | Run immediately | | ๐Ÿ“ฐ Public The New York Times feed | Stable, fast, predictable | | ๐Ÿ–ผ Includes image URLs | Drop straight into dashboards or cards | | โšก Tabular output | CSV, Excel, JSON, XML, no parsing | | ๐Ÿ” Schedule any cadence | Build alerts in minutes | ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Setup | Cost | Output Quality | |---|---|---|---| | Raw RSS parsing | DIY plumbing | Free | Inconsistent | | Paid news APIs | Contract, key | Expensive | Excellent | | **This Actor** | **None** | **Pay-per-use** | **Clean tabular** | ### ๐Ÿš€ How to use 1. [Create a free Apify account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. Open the New York Times Articles Scraper 3. Set `maxItems` (and any other inputs) 4. Click Start 5. Download CSV, Excel, JSON, or XML when finished ### ๐Ÿ’ผ Business use cases #### Media monitoring Track The New York Times headlines on your beats. Push deltas into Slack, Notion, or your internal feed. #### Investment and trading desks Surface market-moving headlines into research dashboards and alerting pipelines. #### Marketing intelligence Watch brand, product, and competitor mentions across the news cycle. #### Content workflows Backfill content libraries, social schedulers, and newsletter tools with fresh headlines. ### ๐Ÿ”Œ Automating New York Times Articles Scraper Pipe results into Make, Zapier, n8n, Slack, Airbyte, GitHub Actions, or Google Drive via the Apify integration catalog. ### ๐ŸŒŸ Beyond business use cases #### Research Build longitudinal corpora for media studies, NLP, and trend analysis. #### Personal Keep a personal news digest of just the topics you care about. #### Non-profit Power advocacy dashboards and rights-monitoring projects. #### Experimentation Train and benchmark summarization, classification, and clustering models on fresh headlines. ### ๐Ÿค– Ask an AI assistant about this scraper Open this Actor's page in [ChatGPT](https://chat.openai.com/), [Claude](https://claude.ai/), [Perplexity](https://www.perplexity.ai/), or [Copilot](https://copilot.microsoft.com/) and ask for help wiring it into your workflow. ### โ“ Frequently Asked Questions **Q: Do I need a The New York Times account?** A: No. The feed is fully public. **Q: How fresh is the data?** A: Mirrors the public The New York Times feed, typically same-hour. **Q: Do I get the full article text?** A: The record includes title, summary, image, author, and URL. Fetch the URL for the full article. **Q: Can I filter by section or topic?** A: This Actor reads the homepage feed. Use other feed URLs in our roadmap for section filtering. **Q: How many articles per run?** A: Up to `maxItems`. Free plan capped at 10. **Q: Can I schedule daily?** A: Yes. Use Apify Schedules. **Q: Can I export to Excel?** A: Yes. Apify exports CSV, Excel, JSON, XML. **Q: Is this affiliated with The New York Times?** A: No. This is an independent tool. **Q: Will it break if the feed changes?** A: We monitor the source and update accordingly. **Q: Does it include images?** A: Yes when the feed exposes a lead image. ### ๐Ÿ”Œ Integrate with any app Apify supports Make, Zapier, n8n, Slack, Airbyte, GitHub Actions, Google Sheets, Google Drive, AWS, Azure, BigQuery, Snowflake, and any webhook-aware tool. ### ๐Ÿ”— Recommended Actors | Actor | What it does | |---|---| | [Reuters News Articles](https://apify.com/parseforge/reuters-articles-scraper) | Latest Reuters headlines | | [AP News Articles](https://apify.com/parseforge/ap-news-articles-scraper) | Associated Press by section | | [BBC News Articles](https://apify.com/parseforge/bbc-news-articles-scraper) | BBC News public feed | | [CNN News Articles](https://apify.com/parseforge/cnn-articles-scraper) | CNN news by section | > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge). **๐Ÿ†˜ Need Help?** [Open our contact form](https://tally.so/r/BzdKgA) > **โš ๏ธ Disclaimer:** This is an independent tool not affiliated with The New York Times. Only publicly available data is collected. # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## Actor input object example ```json { "maxItems": 10 } ``` # 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 = { "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/nyt-articles-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "maxItems": 10 } # Run the Actor and wait for it to finish run = client.actor("parseforge/nyt-articles-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10 }' | apify call parseforge/nyt-articles-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/nyt-articles-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NYT Articles Scraper | New York Times Headlines", "description": "Extract New York Times articles with headline, byline, date, section, abstract, and full content. Filter by section, keyword, or date range. Ideal for media analysts, NLP datasets, sentiment research, and competitive content monitoring across US news.", "version": "0.1", "x-build-id": "JmhzaEUe6nYW66XIF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~nyt-articles-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-nyt-articles-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~nyt-articles-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-nyt-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~nyt-articles-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-nyt-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" } } }, "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 } } } } } } } } } } ```