How to Use the Browse AI MCP in Cursor

Q: How do I add the Browse AI MCP Server to Cursor?

You need to create or edit your .cursor/mcp.json file in your project root. Define the server there, and Cursor will load the tools into your agent. It is the fastest way to get scraping data into your code.

Q: What if my Browse AI task is still running in Cursor?

You can use gettask to poll the status of your extraction job. Once it hits a successful state, the agent can pull the data. You stay informed without manual status checks.

Feed live web scraping results straight into your Cursor project files.

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Connect Browse AI MCP to Cursor

Create your Vinkius account to connect Browse AI 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.

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Setup Browse AI with Cursor

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Claude

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Automate data collection in Cursor

Use `run_robot` to grab data from a target site while you are actively writing code. The AI receives the live JSON output, allowing it to write functions that operate on real-world data. `get_task_data` brings the final payload into your editor workspace. You avoid the friction of jumping between your scraper dashboard and your IDE.

Monitor site changes within Cursor

Call `list_monitors` to track which web pages you are currently watching for updates. It helps you keep your local project synced with external site changes. Use `get_robot` to inspect the configuration of your scrapers without leaving your terminal. You get the technical details you need to adjust your parsing logic instantly.

Execute bulk extractions via Cursor

Run `run_bulk_task` to scrape multiple URLs at once during a massive data gathering phase. It processes everything on the remote infrastructure while you continue your dev work. `download_bulk_data` lets you pull the combined results back into your codebase for processing. You handle large datasets without breaking your coding flow.

Setup guide

Set up Browse AI 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 Browse AI 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 Browse AI transactions." If the MCP tools are loaded correctly, Cursor will call the Browse AI tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "browse-ai-1-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 Browse AI. 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.

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

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

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Common questions about Browse AI MCP in Cursor

You need to create or edit your `.cursor/mcp.json` file in your project root. Define the server there, and Cursor will load the tools into your agent. It is the fastest way to get scraping data into your code.

The AI can read the raw JSON output from your tasks and use that structure to generate code. It creates accurate implementations because it works with real data, not placeholders. You get working logic on the first try.

You can use `get_task` to poll the status of your extraction job. Once it hits a successful state, the agent can pull the data. You stay informed without manual status checks.

Extracted web content flows from the service directly into your editor environment. Your scraped data is never exposed to third-party logs. Security is maintained through local configuration and your private API token.

We keep your API keys out of your project code by using standard environment variables or local config files. Access is restricted to your machine, ensuring your scraping workflow stays private. No one else can see your configurations.

Use it with your favorite AI tools

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