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EasyOCR MCP tool

@WindoC

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基本情報

カテゴリ

その他

トランスポート

stdio

作者

WindoC

投稿者

Antonio Cheong

EasyOCR MCP tool について

A Model Context Protocol (MCP) server that provides OCR capabilities using the EasyOCR library.

#ocr#gpu

EasyOCR MCP tool 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": {
    "easyocr-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/your/project/easyocr-mcp",
        "run",
        "easyocr-mcp.py"
      ],
      "env": {
        "EASYOCR_LANGUAGES": "en,ch_tra,ja"
      }
    }
  }
}

EasyOCR MCP tool 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 EasyOCR MCP Server?

A Model Context Protocol (MCP) server that provides OCR capabilities using the open-source EasyOCR library. It allows AI agents to extract text from images (base64, files, or URLs) with support for over 80 languages.

How to use EasyOCR MCP Server?

Install dependencies with uv sync (optionally install PyTorch with GPU support). Configure language selection via the EASYOCR_LANGUAGES environment variable in your MCP client’s config.json. Run the server with uv run easyocr-mcp.py or mcp run easyocr-mcp.py, then invoke tools: ocr_image_base64, ocr_image_file, or ocr_image_url.

Key features of EasyOCR MCP Server

  • 3 OCR Tools: base64, file, or URL input
  • Multi-language Support: 80+ languages with dynamic selection
  • Flexible Output: text-only or detailed results with coordinates and confidence
  • Performance Optimized: reader caching for better performance
  • Native EasyOCR Output: returns EasyOCR's original format

Use cases of EasyOCR MCP Server

  • Extracting text from scanned documents or photos
  • Reading text from images in multiple languages
  • Automating OCR from image URLs during web scraping
  • Processing base64-encoded images in chat or API workflows

よくある質問

1

How do I select which languages to recognize?

Set the `EASYOCR_LANGUAGES` environment variable to a comma-separated list of language codes (e.g., `en,ch_sim,ja`). Default is English.

2

What output formats are available?

Set the `detail` parameter to `0` for text-only results (list of strings) or `1` for full details (list of tuples containing bounding box coordinates, text, and confidence score).

3

Does the server require a GPU?

GPU usage is determined at installation time based on your PyTorch installation. Install PyTorch with CUDA support to enable GPU acceleration; otherwise the server runs on CPU.

4

How do I process an image from a URL?

Use the `ocr_image_url` tool. The server will fetch the image from the URL and perform OCR automatically.

5

What are the threshold parameters for paragraph detection?

`width_ths` and `height_ths` control how close bounding boxes must be to be merged into a paragraph (default 0.7). The `paragraph` parameter enables paragraph detection (default false).

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