How to Use the Ziflow MCP in Cursor

Q: How does Ziflow integrate with Cursor for development?

You set up the server in your project's .cursor/mcp.json. Once configured, your AI client can call tools like searchproofs and inject live proof data directly into the code you are writing.

Q: Can Ziflow handle multiple types of content review via Cursor?

Yes. You use tools like listintegrationproperties to see all the metadata available on proofs. This allows your agent to build handlers for various asset types.

Q: If I need account data for a project using Ziflow and Cursor, what should I know?

You use getaccountinfo to pull the necessary profile details. This is crucial because your code needs accurate user context before it can proceed with any development task.

Q: How do I get a proof link for Ziflow in Cursor?

Call the getproofviewerurl tool with the relevant ID. The agent returns a clean, ready-to-use string that you can embed directly into your application's code.

Live data context for coding Ziflow workflows in Cursor.

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Connect Ziflow MCP to Cursor

Create your Vinkius account to connect Ziflow 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 Ziflow with Cursor

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Real-time proofing data with the MCP Server.

When you're mid-coding, don't switch tabs to check status. Use the `get_proof` tool within Agent mode. The AI calls Ziflow and injects live details about a specific proof into your current file. This means you aren't working with mock data; you’re building code that uses actual review statuses, making your application logic accurate from the jump.

Manage webhooks and system configuration.

Need to automate when a proof status changes? The `create_webhook` tool lets you set up triggers. You can also use `list_webhooks` to see what's already running in Ziflow. Plus, the `get_account_info` tool gives your agent access to core account profile data, letting you build code that relies on user-specific settings.

Locate and verify contact details through Cursor.

Building a client management system? The `get_contact_by_email` tool finds necessary contact info based on email. This data immediately populates your function's context. If you need to scope out the team, run `list_team_users`. You get an accurate list of users that lets you write roles and permissions logic correctly.

Setup guide

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

.cursor/mcp.json

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ziflow. 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.

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Common questions about Ziflow MCP in Cursor

You set up the server in your project's `.cursor/mcp.json`. Once configured, your AI client can call tools like `search_proofs` and inject live proof data directly into the code you are writing.

Yes. You use tools like `list_integration_properties` to see all the metadata available on proofs. This allows your agent to build handlers for various asset types.

You use `get_account_info` to pull the necessary profile details. This is crucial because your code needs accurate user context before it can proceed with any development task.

This MCP Server primarily touches Proof metadata, which includes asset types, folder structures, and associated team users. This is key for writing accurate code logic.

Call the `get_proof_viewer_url` tool with the relevant ID. The agent returns a clean, ready-to-use string that you can embed directly into your application's code.

Use it with your favorite AI tools

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

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