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MCP server · AI

Image Recognition

by · github.com/mario-andreschak/mcp-image-recognition

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

Unclaimed MIT last commit a year ago ai
InstallView source
54Fair

Scored 5 months ago · breakdown

About Image Recognition

Image Recognition is an MCP server published by mario-andreschak in the AI category: an MCP server that provides image recognition 👀 capabilities using Anthropic and OpenAI vision APIs.

The repository has 40 stars and 13 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/mario-andreschak/mcp-image-recognition

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 23 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • !Dependencies pinnedNo lockfile. Installs can pull different code over time.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

MCP Image Recognition Server

An MCP server that provides image recognition capabilities using Anthropic and OpenAI vision APIs. Version 0.1.2.

Features

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

Requirements

  • Python 3.8 or higher
  • Tesseract OCR (optional) - Required for text extraction feature
    • Windows: Download and install from UB-Mannheim/tesseract
    • Linux: sudo apt-get install tesseract-ocr
    • macOS: brew install tesseract

Installation

  1. Clone the repository:
git clone https://github.com/mario-andreschak/mcp-image-recognition.git
cd mcp-image-recognition
  1. Create and configure your environment file:
cp .env.example .env
# Edit .env with your API keys and preferences
  1. Build the project:
build.bat

Usage

Running the Server

Spawn the server using python:

python -m image_recognition_server.server

Start the server using batch instead:

run.bat server

Start the server in development mode with the MCP Inspector:

run.bat debug

Available Tools

  1. describe_image

    • Input: Base64-encoded image data and MIME type
    • Output: Detailed description of the image

  2. describe_image_from_file

    • Input: Path to an image file
    • Output: Detailed description of the image

Environment Configuration

  • ANTHROPIC_API_KEY: Your Anthropic API key.
  • OPENAI_API_KEY: Your OpenAI API key.
  • VISION_PROVIDER: Primary vision provider (anthropic or openai).
  • FALLBACK_PROVIDER: Optional fallback provider.
  • LOG_LEVEL: Logging level (DEBUG, INFO, WARNING, ERROR).
  • ENABLE_OCR: Enable Tesseract OCR text extraction (true or false).
  • TESSERACT_CMD: Optional custom path to Tesseract executable.
  • OPENAI_MODEL: OpenAI Model (default: gpt-4o-mini). Can use OpenRouter format for other models (e.g., anthropic/claude-3.5-sonnet:beta).
  • OPENAI_BASE_URL: Optional custom base URL for the OpenAI API. Set to https://openrouter.ai/api/v1 for OpenRouter.
  • OPENAI_TIMEOUT: Optional custom timeout (in seconds) for the OpenAI API.

Using OpenRouter

OpenRouter allows you to access various models using the OpenAI API format. To use OpenRouter, follow these steps:

  1. Obtain an OpenAI API key from OpenRouter.
  2. Set OPENAI_API_KEY in your .env file to your OpenRouter API key.
  3. Set OPENAI_BASE_URL to https://openrouter.ai/api/v1.
  4. Set OPENAI_MODEL to the desired model using the OpenRouter format (e.g., anthropic/claude-3.5-sonnet:beta).
  5. Set VISION_PROVIDER to openai.

Default Models

  • Anthropic: claude-3.5-sonnet-beta
  • OpenAI: gpt-4o-mini
  • OpenRouter: Use the anthropic/claude-3.5-sonnet:beta format in OPENAI_MODEL.

Development

Running Tests

Run all tests:

run.bat test

Run specific test suite:

run.bat test server
run.bat test anthropic
run.bat test openai

Docker Support

Build the Docker image:

docker build -t mcp-image-recognition .

Run the container:

docker run -it --env-file .env mcp-image-recognition

License

MIT License - see LICENSE file for details.

Release History

  • 0.1.2 (2025-02-20): Improved OCR error handling and added comprehensive test coverage for OCR functionality
  • 0.1.1 (2025-02-19): Added Tesseract OCR support for text extraction from images (optional feature)
  • 0.1.0 (2025-02-19): Initial release with Anthropic and OpenAI vision support

README fetched from the repository 23 hours ago. The original is authoritative.

Questions

About Image Recognition

How do I install Image Recognition?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Image Recognition safe to use with an AI agent?

Its trust score is 54 out of 100 (fair). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Image Recognition still maintained?

The last commit was a year ago and 1 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.