How to Use the Affinda MCP in Cursor

Q: How do I configure Affinda for Cursor?

Create an mcp.json file in your project root directory. Add the Affinda MCP server configuration there. Turn on Agent mode in the chat panel to activate the tools.

Inject parsed invoice data directly into your codebase using Cursor and this MCP Server.

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Connect Affinda MCP to Cursor

Create your Vinkius account to connect Affinda 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 Affinda with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Parse complex documents from Cursor

Affinda handles intelligent document extraction via MCP so you can build features faster. When you prompt Cursor to write an importer script, the AI runs `create_document` to process a test PDF via URL. It sees the real JSON structure instead of guessing what the API returns. Getting the results is just as fast. The agent fires off `get_document` to pull the fully structured data. Your editor writes the exact TypeScript interfaces based on the actual parsed fields, saving you hours of trial and error.

Query your Affinda MCP Server models

Different files require different parsing models. Cursor checks your available options by executing `list_document_types` in the background. If you need to support passports, the AI confirms the model exists before writing the implementation code. Organizing these test runs happens automatically. The `list_workspaces` tool lets Cursor find the right container for your development environment. Your AI agent writes code that targets the correct workspace ID without you digging through documentation.

Audit processed files in your editor

Testing an integration means checking if files actually went through. Cursor uses the MCP protocol to verify that your test invoices parsed correctly by calling `list_documents`. The agent reads the processing status straight from the API. You see the results right next to your code. If a test file fails, the AI client spots the error in the returned JSON and suggests a fix for your upload logic. You stay in the editor the whole time.

Setup guide

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

.cursor/mcp.json

{
  "mcpServers": {
    "affinda-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 Affinda. 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 Affinda MCP in Cursor

Create an `mcp.json` file in your project root directory. Add the Affinda MCP server configuration there. Turn on Agent mode in the chat panel to activate the tools.

Yes. The editor pulls the live JSON response and writes the exact interfaces for you. You get accurate types based on real parsed documents.

No. The agent hits the real API to get actual responses. You build against live parsed data instead of hardcoded stubs.

The agent reads the failure status directly from the API response. It then suggests code changes to fix your upload logic.

Tax IDs and billing amounts remain isolated during the entire process. The zero-trust architecture guarantees that your API tokens and document contents never leak to unauthorized clients. Ephemeral connections close the moment the extraction finishes.

Use it with your favorite AI tools

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

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