nvidia-vision-mcp

nvidia-vision-mcp

Enables AI models to read local images using NVIDIA vision models, supporting image description, text extraction, and custom analysis.

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NVIDIA Vision MCP

A small MCP server for reading local images with NVIDIA vision models.

This is useful when the AI model you are using cannot see images directly. A common case is browser debugging: Chrome DevTools can capture a screenshot, but the model still cannot inspect what is inside the image. This server gives the model a simple way to read that screenshot.

What It Does

  • Describes local images and screenshots
  • Extracts visible text from images
  • Answers specific questions about an image
  • Deletes temporary screenshot files after use

Setup

Add the server to your MCP client config:

{
  "mcpServers": {
    "nvidia-vision": {
      "command": "npx",
      "args": ["-y", "nvidia-vision-mcp"],
      "env": {
        "NVIDIA_MODEL": "meta/llama-4-maverick-17b-128e-instruct",
        "NVIDIA_API_KEY": "your_nvidia_api_key"
      }
    }
  }
}

The API key is read from the MCP server environment. No .env file is needed.

NVIDIA_MODEL is optional. If it is not set, the server uses:

meta/llama-4-maverick-17b-128e-instruct

You can replace it with another NVIDIA-hosted vision-capable chat model when needed.

For local development from this folder:

{
  "mcpServers": {
    "nvidia-vision": {
      "command": "node",
      "args": ["/path/to/nvidia-vision/src/server.js"],
      "env": {
        "NVIDIA_MODEL": "meta/llama-4-maverick-17b-128e-instruct",
        "NVIDIA_API_KEY": "your_nvidia_api_key"
      }
    }
  }
}

Tools

describe_image

Describes what is visible in a local image.

extract_text_from_image

Extracts text from an image or screenshot. Useful for UI errors, terminal output, form labels, dialogs, and short documents.

analyze_image

Answers a custom question about an image. For example, you can ask where a button is, what color an element uses, or whether an error message is visible.

delete_file

Deletes a local file. This is mostly for cleaning up temporary screenshots.

Examples

Read text from a screenshot:

extract_text_from_image(image_path="/tmp/screenshot.png")

Ask about a specific part of the UI:

analyze_image(
  image_path="/tmp/screenshot.png",
  question="What does the primary button say, and where is it located?"
)

Describe a screenshot and remove it afterwards:

describe_image(image_path="/tmp/screenshot.png", cleanup=true)

Notes

This server intentionally stays narrow. It exists to help models inspect local screenshots when another tool can produce the image file but cannot explain what is inside it.

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