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RapidOCR MCP Server

RapidOCR MCP Server

Local
github.com/z4noneMedia & Design6Updated 59w ago
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About RapidOCR MCP Server

RapidOCR MCP Server exposes RapidOCR-based image text recognition through two methods: one accepts base64 image content and the other a file path. It is for MCP clients that need OCR results from images.

Key features

  1. 01OCR from base64 image content
  2. 02OCR from an image file path

Use cases

  1. 01Extract text from supplied image content
  2. 02Read text from an image file

MCP support

The MCP server exposes two OCR methods to clients: one processes base64-encoded image content, and the other processes an image file specified by path.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "rapidocr": {
      "command": "uvx",
      "args": [
        "run"
      ]
    }
  }
}
Run commanduvx run

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypirun

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

RapidOCR MCP Server

A MCP server based on RapidOCR, providing an easy-to-use OCR interface.

Usage

uvx run rapidocr-mcp

MCP config

"rapidocr-mcp": {
    "command": "uvx",
    "args": [
    "rapidocr-mcp"
    ],
    "env": {}
}

Screenshots

config usage

Available Methods

  • ocr_by_content Perform OCR on an image content. Args: base64_data (str): The base64 encoded image content. Returns: List[TextContent]: A list of text content.

  • ocr_by_path Perform OCR on an image file. Args: path (str): The path to the image file. Returns: List[TextContent]: A list of text content.

remark

Currently, large language models are becoming increasingly powerful and generally possess multimodal capabilities, enabling them to recognize text in images without the need for external OCR tools.

Comments

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