How to Use the Groq MCP in Cursor

Q: How do I add the Groq MCP Server to my Cursor editor?

Add the server configuration to your global /.cursor/mcp.json file or your project-specific config. Once configured, Cursor's agent mode immediately gains access to all ten tools.

Q: Does Groq code generation in Cursor support Llama 3?

Yes. The createchatcompletion tool uses Groq's optimized Llama 3 models to write and edit code blocks inside Cursor.

Q: Can I inspect the active models?

Yes, the listavailablemodels tool lets you view all active high-performance models.

Inject Groq's lightning-fast code generation tools straight into Cursor to write and explain code inside your active workspace.

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Connect Groq MCP to Cursor

Create your Vinkius account to connect Groq 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 Groq with Cursor

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LPU-Powered MCP Server Tools in Cursor

The `generate_code` tool writes clean, functional code blocks directly inside your Cursor editor window. Your agent calls this tool to generate scripts from raw comments, bypassing the typical lag of standard LLM providers. When you need to understand legacy files, Cursor uses `explain_code` to break down logic step-by-step. This MCP Server integration ensures your agent has the speed to analyze large codebases without stalling your editor.

On-the-Fly Text Refactoring and Translation

The `fix_grammar` tool cleans up documentation, markdown files, and inline comments directly inside your Cursor workspace. Your agent fixes typos and phrasing issues instantly, keeping your commit messages and docs clean. If you work with international teams, the agent runs `translate_text` to convert comments or localization files. Having this MCP Server connected means your editor handles multi-language translation without external API clients.

LPU-Powered Model Management in Cursor

The `list_available_models` tool queries Groq's current lineup of high-speed models directly from your Cursor terminal. Your agent checks which models are active so you always route your tasks to the fastest available hardware. Your agent runs `get_model_details` to inspect context limits and hardware specs before launching heavy generation jobs. This gives your editor deep insight into the remote inference engine.

Setup guide

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

.cursor/mcp.json

{
  "mcpServers": {
    "groq-alternative-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 Groq. 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 Groq MCP in Cursor

Add the server configuration to your global `~/.cursor/mcp.json` file or your project-specific config. Once configured, Cursor's agent mode immediately gains access to all ten tools.

Yes. The `create_chat_completion` tool uses Groq's optimized Llama 3 models to write and edit code blocks inside Cursor.

Raw speed is the main reason. Groq's LPU hardware processes code completions and refactoring tasks significantly faster than traditional cloud GPU setups.

Yes, the `list_available_models` tool lets you view all active high-performance models.

Yes, your raw source code is only sent to Groq's secure endpoints to execute the requested tool. The Vinkius runtime environment uses ephemeral sandboxing, ensuring no code snippets are cached or stored on external servers.

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