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.

Category
访问服务器

README

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.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选