NVIDIA MCP Bridge

A Model Context Protocol (MCP) server that bridges Antigravity and other MCP clients to NVIDIA's NIM (NVIDIA Inference Microservices) API. This bridge enables high-performance reasoning and coding assistance using state-of-the-art open models.

Features

Multi-Model Support: Direct access to Google's Gemma 4 31B and DeepSeek V4 Pro.
Thinking Mode: Automatically enables "thinking/reasoning" capabilities for Gemma 4 via NVIDIA NIM's chat template kwargs.
Dynamic Token Budgets: Scalable output budgets from 4k up to 128k (for DeepSeek) to handle everything from quick Q&A to massive file refactors.
Smart Rate-Limiting: Built-in proactive throttling at 35 RPM to stay safely within NVIDIA's 40 RPM free tier limits.
Automatic Heuristics: DeepSeek tool automatically scales its token budget based on input size for large codebase context.
Real-time Logging: Stderr logging to verify tool calls, model selection, and token counts in real-time.

Installation

Clone the repository:

git clone <repository-url>
cd nvidia-mcp-bridge

Install dependencies:
```
npm install
```
Get an NVIDIA API Key: Visit build.nvidia.com to generate your free API key.

Configuration

Environment Variables

The server requires:

NVIDIA_API_KEY: Your NVIDIA NIM API key.

Adding to Antigravity

Add the bridge to your Antigravity configuration file.

Path: C:\Users\<YourUsername>\.gemini\antigravity\mcp_config.json

{
  "mcpServers": {
    "nvidia-bridge": {
      "command": "C:/Program Files/nodejs/node.exe",
      "args": [
        "D:/Projects/nvidia-mcp-bridge/index.js"
      ],
      "cwd": "D:/Projects/nvidia-mcp-bridge",
      "env": {
        "NVIDIA_API_KEY": "your-api-key-here"
      }
    }
  }
}

[!IMPORTANT] Ensure the path to index.js in args and the cwd match the actual location of the project on your system.

Quick Test

Verify the bridge is working by asking:

@nvidia-bridge: tell me about yourself.

Available Tools

`ask_gemma_4`

Query Google's Gemma 4 31B model. Best for high-speed logical reasoning and everyday coding tasks.

Prompt: (Required) The task or question.
max_tokens: (Optional) 4096 (Default), 8192, 16384 (Deep Thinking), up to 32768.

`ask_deepseek_v4`

Query DeepSeek AI V4 Pro. Optimized for intense software engineering, large multi-file edits, and complex logic.

Prompt: (Required) The task or codebase context.
max_tokens: (Optional) 8192 (Default), 16384, 32768 (Large modules), up to 131072.

How to Force a Specific Model (Optional)

If you want absolute control and don't want the agent to guess, you can bypass its decision-making entirely by naming the specific tool in your prompt:

To guarantee Gemma 4: @nvidia-bridge use ask_gemma_4 to explain this regex pattern.
To guarantee DeepSeek V4 Pro: @nvidia-bridge use ask_deepseek_v4 to debug this async race condition.

Summary Checklist

Normal Chat (No @): Always uses native Gemini.
Typing @nvidia-bridge: Let the AI Agent pick between Gemma 4 or DeepSeek V4 based on the complexity of your prompt.
Typing @nvidia-bridge use ask_[model]: Forces the exact model you want.

Model Comparison

Development

# Run locally to verify setup
node index.js

License

Apache 2.0

MCP Servers