Nvidia Vision
БесплатноНе проверенEnables AI models to read local images using NVIDIA vision models, supporting image description, text extraction, and custom analysis.
Описание
Enables AI models to read local images using NVIDIA vision models, supporting image description, text extraction, and custom analysis.
README
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
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 settarget, 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.
Установить Nvidia Vision в Claude Desktop, Claude Code, Cursor
unyly install nvidia-vision-mcpСтавит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.
Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh
Или настроить вручную
Выполни в терминале:
claude mcp add nvidia-vision-mcp -- npx -y nvidia-vision-mcpFAQ
Nvidia Vision MCP бесплатный?
Да, Nvidia Vision MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Nvidia Vision?
Нет, Nvidia Vision работает без API-ключей и переменных окружения.
Nvidia Vision — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Nvidia Vision в Claude Desktop, Claude Code или Cursor?
Открой Nvidia Vision на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Omni Video
An MCP server that transforms LLM-enabled IDEs into professional video editors by pre-processing footage into text proxies, generating motion graphics via HTML/
автор: buildwithtazaARA
Generate images, video and audio from any AI agent — one connector.
автор: ARAYouTube
Transcripts, channel stats, search
автор: YouTubeEverArt
AI image generation using various models.
автор: modelcontextprotocolCompare Nvidia Vision with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории media
