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handwriting-ocr-mcp-server
Model Context Protocol (MCP) Server for Handwriting OCR
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Handwriting OCR MCP Server
A Model Context Protocol (MCP) Server for Handwriting OCR API.
Overview
The Handwriting OCR MCP Server enables integration between MCP clients and the Handwriting OCR service. This document outlines the setup process and provides a basic example of using the client.
This server allows you to upload images and PDF documents, check their status, and retrieve the OCR result as Markdown.
Tools
Transcription
- Upload Document
- Check Status
- Get Text
Prerequisites
Before you begin, ensure you have the following:
- Node.js installed on your system (recommended version 18.x or higher).
- An active account on the Handwriting OCR Platform and an active API token.
Installation
Installing via Smithery
To install handwriting-ocr-mcp-server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @Handwriting-OCR/handwriting-ocr-mcp-server --client claude
Installing manually for Claude Desktop
To use the Handwriting OCR MCP Server in Claude Desktop application, use:
{
"mcpServers": {
"handwriting-ocr": {
"command": "node",
"args": [
"/Users/mateo/Local/Code/MCP/handwriting-ocr/build/index.js"
],
"env": {
"API_TOKEN": "your-api-token",
},
"disabled": false,
"autoApprove": []
}
}
}
Configuration
The Handwriting OCR MCP Server supports environment variables to be set for authentication and configuration:
-
API_TOKEN
: Your API token.
You can find these values in the API settings dashboard on the Handwriting OCR Platform.
Support
Please refer to the Handwriting OCR API Documentation.
For support with the Handwriting OCR MCP Server, please submit a GitHub Issue.
About
Model Context Protocol (MCP) Server for Handwriting OCR Platform
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Reviews

user_8ktoFGFC
Handwriting-OCR MCP Server is a game-changer for converting handwritten text to digital format with impressive accuracy and efficiency. Handwriting-OCR has created an exceptional tool that seamlessly integrates with various applications, and the GitHub repository provides extensive documentation to get started quickly. Highly recommended for anyone needing reliable handwriting OCR capabilities!