MCP Image Recognition Server

Name: MCP Image Recognition Server
Author: mario-andreschak

@mario-andreschak

代码仓库

关于 MCP Image Recognition Server

An MCP server that provides image recognition 👀 capabilities using Anthropic and OpenAI vision APIs

基本信息

分类

媒体与设计

许可证

MIT

运行时

python

传输方式

stdio

发布者

mario-andreschak

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-image-recognition": {
      "command": "python",
      "args": [
        "-m",
        "image_recognition_server.server"
      ]
    }
  }
}

工具

Base64-encoded image data and MIME type

Detailed description of the image

Path to an image file

Detailed description of the image

概览

What is MCP Image Recognition Server?

An MCP server that provides image recognition capabilities using Anthropic and OpenAI vision APIs. It supports multiple image formats and optional OCR text extraction via Tesseract.

How to use MCP Image Recognition Server?

Clone the repository, copy .env.example to .env, set API keys and preferences, then build and run via python -m image_recognition_server.server or run.bat server. Use tools describe_image (base64 input) and describe_image_from_file (file path). Environment variables control provider, model, OCR, and logging.

Key features of MCP Image Recognition Server

Image description using Claude Vision or GPT-4 Vision
Support for JPEG, PNG, GIF, WebP formats
Configurable primary and fallback provider (Anthropic/OpenAI)
Base64 and file-based image input
Optional Tesseract OCR text extraction
OpenRouter support for additional models

Use cases of MCP Image Recognition Server

Automatically describing images in chat or workflow applications
Extracting text from images using optional OCR
Integrating vision capabilities into MCP-powered tools
Reliable image analysis with fallback provider

FAQ from MCP Image Recognition Server

What are the runtime requirements?

Python 3.8 or higher is required. Tesseract OCR is optional and only needed for text extraction.

How do I configure the vision provider?

Set VISION_PROVIDER to anthropic or openai in the .env file. Optionally set FALLBACK_PROVIDER for a secondary provider.

Can I use models other than the defaults?

Yes, via OpenRouter: set OPENAI_BASE_URL to https://openrouter.ai/api/v1, OPENAI_MODEL to the desired model (e.g., anthropic/claude-3.5-sonnet:beta), and VISION_PROVIDER to openai.

Does the server support Docker?

Yes. Build the image with docker build -t mcp-image-recognition . and run with docker run -it --env-file .env mcp-image-recognition.

What image formats are supported?

JPEG, PNG, GIF, and WebP are supported for both base64 and file-based input.

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