How to Use the LLM ROUGE & BLEU Evaluator MCP in Cursor

Q: How do I configure the LLM ROUGE & BLEU Evaluator in Cursor?

Add the server to your .cursor/mcp.json file in your project root. Cursor will automatically detect the MCP Server and make the calculaterougebleu tool available in Agent mode.

Q: Can the LLM ROUGE & BLEU Evaluator help me debug prompts inside Cursor?

Yes. You can ask Cursor to run calculaterougebleu on different prompt variations to see which one yields the highest n-gram overlap.

Compare model outputs against reference text inside Cursor using real-time mathematical scoring.

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Connect LLM ROUGE & BLEU Evaluator MCP to Cursor

Create your Vinkius account to connect LLM ROUGE & BLEU Evaluator 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 LLM ROUGE & BLEU Evaluator with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Inline code generation validation in Cursor

Writing prompt engineering code in Cursor gets tricky when you cannot verify output quality on the fly. This MCP Server lets your editor run `calculate_rouge_bleu` directly against your test files. Instead of guessing if your code changes improved the model, you can ask Cursor to run the math. The editor calls the tool to provide precise overlap metrics while you write code.

Agentic test suite execution

When you use Cursor in Agent mode, the AI can actively run your evaluation pipeline. It uses `calculate_rouge_bleu` to compare candidate strings generated by your local server against reference files. This MCP setup turns Cursor into an interactive test runner. You see immediate mathematical feedback on your prompt changes without context-switching to a terminal.

Zero-stub integration with live API responses

Instead of using mock data, Cursor pulls real outputs from your local development server. The editor then feeds those live responses directly into the `calculate_rouge_bleu` tool. You get real-world metrics based on actual outputs. This ensures your prompt evaluations match what your users will eventually see in production.

Setup guide

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

.cursor/mcp.json

{
  "mcpServers": {
    "llm-rouge-bleu-evaluator-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about LLM ROUGE & BLEU Evaluator MCP in Cursor

Add the server to your `.cursor/mcp.json` file in your project root. Cursor will automatically detect the MCP Server and make the `calculate_rouge_bleu` tool available in Agent mode.

Yes. You can ask Cursor to run `calculate_rouge_bleu` on different prompt variations to see which one yields the highest n-gram overlap.

It runs locally through the configured MCP Server process in your project. This keeps the execution of `calculate_rouge_bleu` fast and secure within your workspace.

The tool tokenizes your candidate and reference strings using standard whitespace rules. It then calculates the exact mathematical overlap to output BLEU and ROUGE metrics.

Absolutely not. Your candidate and reference text strings are processed locally by the server running inside your Cursor environment, ensuring complete data isolation.

Use it with your favorite AI tools

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

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