# RapidOCR

> Use this tool when you need to extract text from images or automate document processing. RapidOCR provides optical character recognition capabilities, accepting base64-encoded image data or file paths as input and returning recognized text as output. It is ideal for workflows requiring automated text extraction from images, such as document scanning or image-based data entry.

Canonical page: https://skillsregistry.net/skills/z4none-rapidocr  
JSON: https://api.skillsregistry.net/v1/skills/z4none-rapidocr

## Description

RapidOCR MCP Server provides optical character recognition capabilities through a simple interface built on the RapidOCR library. It exposes two main tools: ocr_by_content for processing base64-encoded image data and ocr_by_path for analyzing images from file paths. The server runs using the MCP transport protocol over stdio, making it compatible with various client applications. This implementation is particularly useful for extracting text from images in workflows that require automated document processing or image-based text extraction.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/z4none-rapidocr)
- **Repository:** <https://github.com/z4none/rapidocr-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "z4none-rapidocr"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/z4none-rapidocr` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/z4none-rapidocr/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt