Which integrations are available for this server?

Allows image analysis, comparison, OCR, and scene description using Google Gemini's vision models (e.g., Gemini Pro Vision) via OpenRouter. Allows image analysis, comparison, OCR, and scene description using locally hosted vision models via Ollama (e.g., LLaVA). Allows image analysis, comparison, OCR, and scene description using OpenAI's vision models (e.g., GPT-4o).

How do I use vision-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@vision-mcp Describe what's in this image" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

vision-mcp

by cpramod

Overview Schema Related Servers Score Discussions

JavaScript

Remote

Vision MCP

A Model Context Protocol (MCP) server that provides image analysis capabilities using vision-capable AI models.

Features

Image Analysis: Analyze images for objects, text, colors, and context
Image Comparison: Compare multiple images and identify differences
Text Extraction (OCR): Extract text from images with formatting preservation
Scene Description: Get detailed descriptions of scenes and settings

Related MCP server: vision-mcp-server

Installation

Option 1: Use directly with npx (no install needed)

Add to Claude Desktop config:

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-api-key",
        "OPENAI_BASE_URL": "https://api.openai.com/v1",
        "VISION_MODEL": "gpt-4o"
      }
    }
  }
}

Option 2: Install globally from GitHub

npm install -g github:cpramod/vision-mcp

Then use in Claude Desktop config:

{
  "mcpServers": {
    "vision": {
      "command": "vision-mcp",
      "env": {
        "OPENAI_API_KEY": "your-api-key",
        "OPENAI_BASE_URL": "https://api.openai.com/v1",
        "VISION_MODEL": "gpt-4o"
      }
    }
  }
}

Option 3: Install from local clone

git clone https://github.com/cpramod/vision-mcp.git
cd vision-mcp
npm install
npm run build

Then use the local path in Claude Desktop config:

{
  "mcpServers": {
    "vision": {
      "command": "node",
      "args": ["/path/to/vision-mcp/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "your-api-key",
        "OPENAI_BASE_URL": "https://api.openai.com/v1",
        "VISION_MODEL": "gpt-4o"
      }
    }
  }
}

Configuration

Environment Variables

Variable	Description	Required
`OPENAI_API_KEY` or `API_KEY`	API key for the vision provider	For most providers
`OPENAI_BASE_URL` or `API_BASE_URL`	Custom API endpoint URL	No (defaults to OpenAI)
`VISION_MODEL` or `MODEL`	Model name to use	No (defaults to `gpt-4o`)

Usage with Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

OpenAI:

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "VISION_MODEL": "gpt-4o"
      }
    }
  }
}

Anthropic Claude via OpenRouter:

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_BASE_URL": "https://openrouter.ai/api/v1",
        "OPENAI_API_KEY": "your-openrouter-key",
        "VISION_MODEL": "anthropic/claude-3.5-sonnet"
      }
    }
  }
}

Google Gemini via OpenRouter:

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_BASE_URL": "https://openrouter.ai/api/v1",
        "OPENAI_API_KEY": "your-openrouter-key",
        "VISION_MODEL": "google/gemini-pro-vision"
      }
    }
  }
}

Ollama (local):

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_BASE_URL": "http://localhost:11434/v1",
        "VISION_MODEL": "llava"
      }
    }
  }
}

Groq:

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_BASE_URL": "https://api.groq.com/openai/v1",
        "OPENAI_API_KEY": "your-groq-key",
        "VISION_MODEL": "llama-3.2-11b-vision-preview"
      }
    }
  }
}

LM Studio (local):

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["github:cpramod/vision-mcp"],
      "env": {
        "OPENAI_BASE_URL": "http://localhost:1234/v1",
        "VISION_MODEL": "local-model"
      }
    }
  }
}

Available Tools

analyze_image

Analyze an image using vision AI.

Parameters:

image (required): URL or base64-encoded image data
prompt (optional): Custom analysis prompt
detail (optional): "low", "high", or "auto" detail level

Example:

{
  "name": "analyze_image",
  "arguments": {
    "image": "https://example.com/image.jpg",
    "prompt": "What's in this image?"
  }
}

compare_images

Compare 2-4 images.

Parameters:

images (required): Array of image URLs or base64 data (2-4 images)
prompt (optional): Custom comparison prompt

extract_text

Extract text from images (OCR).

Parameters:

image (required): URL or base64-encoded image
preserve_formatting (optional): Maintain layout (default: true)

describe_scene

Get detailed scene descriptions.

Parameters:

image (required): URL or base64-encoded image
focus (optional): Focus area (e.g., "people", "architecture")

Supported Image Formats

JPEG, PNG, GIF, WebP
URLs or base64-encoded data URIs

Development

npm run dev    # Build and run
npm run build  # Compile TypeScript
npm start      # Run compiled server

Publishing to npm (optional)

npm login
npm publish

After publishing to npm, users can install with:

{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["vision-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-api-key",
        "OPENAI_BASE_URL": "https://api.openai.com/v1",
        "VISION_MODEL": "gpt-4o"
      }
    }
  }
}

This server cannot be installed

license - permissive license

quality - not tested

maintenance

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Maintenance

–Maintainers

4dResponse time

–Release cycle

–Releases (12mo)

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