How to Use the New York Times MCP in Cursor

Q: Can I use Cursor to test New York Times API integrations?

Yes, Cursor uses this MCP Server to run live queries like searcharticles while you write code. You can inspect the actual New York Times payload format directly in your editor.

Q: How does Cursor fetch older New York Times articles?

The editor triggers getarchive for the specific year and month you need. Cursor pulls the New York Times archival data to help you build historical datasets.

Q: Can Cursor help me format New York Times book lists?

Absolutely, Cursor calls getbooklists to grab the raw data. It then writes the TypeScript interfaces or JSON schemas based on the actual New York Times response.

Inject live New York Times data and article metadata directly into your Cursor workspace while you write code.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect New York Times MCP to Cursor

Create your Vinkius account to connect New York Times to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup New York Times with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build news-driven apps inside the Cursor editor

The `get_top_stories` tool pulls live New York Times headlines directly into your Cursor workspace while you write code. You get real New York Times data to test your components inside Cursor, rather than relying on mock JSON for your news aggregator projects. This New York Times MCP Server integration allows your Cursor editor to understand the actual shape of the news payload. You can write your parsing logic while Cursor validates it against real-time New York Times data.

Query New York Times sections while coding in Cursor

Running `get_sections` maps out your application's category structure dynamically inside the Cursor editor using live New York Times sections. Cursor can fetch the complete, current list of New York Times news categories so you avoid hardcoding outdated endpoints. If you need to test how your app handles specific topics, Cursor uses `get_top_stories` to fetch those New York Times section names. You get instant feedback in Cursor using live New York Times content.

Track reading trends directly within Cursor

The `get_most_shared` tool uses this New York Times MCP Server to inject real viral metrics into your database seeds inside Cursor. Cursor invokes this or `get_most_viewed` to pull the most popular New York Times pieces of the week so your code gets populated with actual trending URLs. You can also use `get_most_emailed` to test how your notification service handles high-priority New York Times articles directly in Cursor. Cursor handles the New York Times API calls in the background while you code.

Setup guide

Set up New York Times MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the New York Times MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent New York Times transactions." If the MCP tools are loaded correctly, Cursor will call the New York Times tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "new-york-times-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by New York Times. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect New York Times now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about New York Times MCP in Cursor

Yes, Cursor uses this MCP Server to run live queries like `search_articles` while you write code. You can inspect the actual New York Times payload format directly in your editor.

The editor triggers `get_archive` for the specific year and month you need. Cursor pulls the New York Times archival data to help you build historical datasets.

Absolutely, Cursor calls `get_book_lists` to grab the raw data. It then writes the TypeScript interfaces or JSON schemas based on the actual New York Times response.

You place your New York Times developer key in your local MCP configuration. Cursor reads it securely to authenticate your API requests.

Cursor does not store any of your New York Times search queries or API keys. The Vinkius sandbox ensures your raw article queries from Cursor pass directly to the publisher without leaving a trace on external servers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript