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

• Turns a UI screenshot into code, a prompt, a spec, or a description

• OCRs screenshots optimized for code, terminal output, documents, or general text

• Diagnoses error screenshots and proposes fixes

• Interprets technical diagrams (architecture, flow, UML, ER, sequence, system)

• Reads charts and dashboards to surface insights and trends

• Compares two UI screenshots to flag visual drift

• General-purpose image understanding as a fallback

• Deletes temporary screenshot files after use

Related MCP server: vision-reader

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.

ui_to_artifact

Turns a UI screenshot into a reusable artifact. Choose artifact_type:

• code — production-ready code recreating the UI (optionally set target, e.g. react + tailwind).

• prompt — a text-to-UI prompt that reproduces the screenshot.

• spec — a structured UI specification.

• description — a written description for documentation.

extract_text_from_screenshot

OCR tuned for a specific kind of content: code, terminal, document, or general (default). Reproduces text verbatim with structure preserved.

diagnose_error_screenshot

Analyzes an error snapshot (stack trace, crash dialog, failed build, browser console). Extracts the error, explains it, finds the likely root cause, and lists ordered fix steps. Pass optional context for what was being attempted.

understand_technical_diagram

Interprets a technical diagram. Set diagram_type to architecture, flow, uml, er, sequence, system, or auto (default). Optionally ask a follow-up question.

analyze_data_visualization

Reads a chart, graph, or dashboard. Reports visualization type, axes/units, key values, trends, and insights. Optionally answer a specific question. Will not fabricate unreadable numbers.

ui_diff_check

Compares two UI screenshots (image_path_a / image_path_b) and flags visual or implementation drift, with per-difference severity and recommendations. Optionally focus on an aspect like spacing, colors, layout, or typography.

image_analysis

General-purpose image understanding when a more specific tool does not fit. Pass any freeform task instruction.

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)

Turn a UI screenshot into React + Tailwind code:

ui_to_artifact(
  image_path="/tmp/screenshot.png",
  artifact_type="code",
  target="react + tailwind"
)

OCR terminal output from a screenshot:

extract_text_from_screenshot(image_path="/tmp/terminal.png", kind="terminal")

Diagnose a build error screenshot with context:

diagnose_error_screenshot(
  image_path="/tmp/build-error.png",
  context="Running vite build on a React + TypeScript project"
)

Compare two versions of a UI:

ui_diff_check(
  image_path_a="/tmp/before.png",
  image_path_b="/tmp/after.png",
  focus="spacing"
)

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.