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MCP Server - Image

@IA-Programming

リポジトリ

基本情報

カテゴリ

メディアとデザイン

ライセンス

MIT license

トランスポート

stdio

作者

IA-Programming

MCP Server - Image について

## MCP-Images Looking for a powerful image processing server? MCP Server-Image provides enterprise-grade image handling with just a few lines of code. Perfect for AI applications, web services, and data processing pipelines. [Get Started](#installation) | [Support Us](

#image#mcp#image-processing#image-manipulation

MCP Server - Image の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-images": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

MCP Server - Image のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Server - Image?

A Model Context Protocol (MCP) server that provides tools for fetching and processing images from URLs, local file paths, and numpy arrays. It includes a tool called fetch_images that returns images as base64-encoded strings along with their MIME types.

How to use MCP Server - Image?

Prerequisites: Python 3.10+ and the uv package manager. Clone the repository, create and activate a virtual environment with uv, then install dependencies from requirements.txt. Run the server directly with uv run python mcp_image.py. For integration with Windsurf or Cursor, add a JSON configuration entry pointing to the server script.

Key features of MCP Server - Image

  • Fetch images from HTTP/HTTPS URLs
  • Load images from local file paths
  • Specialized handling for large local images
  • Automatic image compression for images >1MB
  • Parallel processing of multiple images
  • Proper MIME type mapping for file extensions
  • Comprehensive error handling and logging

Use cases of MCP Server - Image

  • Fetch and process images from multiple URLs in a single request
  • Load and process local images for AI assistant workflows
  • Combine URL and local file images for unified processing

よくある質問

1

What are the prerequisites for running the server?

Python 3.10 or later and the uv package manager are required.

2

How do I configure the server for Windsurf or Cursor?

Edit the `mcp_config.json` file for Windsurf or add a new MCP server in Cursor settings, providing the command `uv` with arguments pointing to the server directory and script.

3

What does the fetch_images tool return?

It returns a list of processed images, each as a base64-encoded string with its corresponding MIME type.

4

How are large images handled?

Images larger than 1MB are automatically compressed to reduce size.

5

What image sources are supported?

Images can be sourced from URLs (http/https), local file paths, and numpy arrays.

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