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RapidOCR MCP Server

by bitfarer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
RAPIDOCR_LANGNoOCR language, e.g., 'ch' for Chinese.
RAPIDOCR_API_KEYNoAPI key for authentication.
RAPIDOCR_LOG_LEVELNoLog level, e.g., 'INFO'.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
ocr_by_pathA

对本地图像文件执行 OCR 识别。

Args:
    image_path: 图像文件的绝对路径或相对路径
    output_format: 输出格式 (plain/json/markdown/structured)
    auto_enhance: 自动增强图像对比度和锐度
    rotate: 自动旋转图像（基于 EXIF）
    binarize: 二值化图像

Returns:
    OCR 识别结果
ocr_by_contentA

对 Base64 编码的图像执行 OCR 识别。

Args:
    image_base64: Base64 编码的图像（支持 data:image/... 前缀）
    output_format: 输出格式 (plain/json/markdown/structured)
    auto_enhance: 自动增强图像对比度和锐度
    rotate: 自动旋转图像（基于 EXIF）
    binarize: 二值化图像

Returns:
    OCR 识别结果
ocr_by_urlA

对 URL 图像执行 OCR 识别。

Args:
    image_url: 图像的 HTTP/HTTPS URL
    output_format: 输出格式 (plain/json/markdown/structured)
    use_cache: 是否使用 URL 缓存
    auto_enhance: 自动增强图像对比度和锐度
    rotate: 自动旋转图像（基于 EXIF）
    binarize: 二值化图像

Returns:
    OCR 识别结果
ocr_batchA

批量 OCR - 对多张图像执行 OCR 识别。

Args:
    image_paths: 图像文件路径列表
    output_format: 输出格式 (plain/json/markdown/structured)
    auto_enhance: 自动增强图像对比度和锐度
    rotate: 自动旋转图像（基于 EXIF）
    binarize: 二值化图像

Returns:
    所有图像的 OCR 识别结果

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored across 4 tools

Disambiguation5/5

Each tool targets a distinct input source: local file path, base64 content, URL, and batch of paths. The descriptions clearly differentiate the tools, and the batch tool's multi-image purpose avoids confusion with single-image processing.

Naming Consistency4/5

Three tools follow the 'ocr_by_<source>' pattern clearly, but 'ocr_batch' deviates by omitting 'by'. This is a minor inconsistency that does not harm readability.

Tool Count5/5

Four tools are well-scoped for an OCR server, covering the primary input methods (file, content, URL, batch) without unnecessary redundancy. The count feels complete and focused.

Completeness5/5

The tool surface covers the core OCR workflows for local files, base64 data, URLs, and batch processing. There are no obvious gaps for a typical OCR use case, making the set comprehensive.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources