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Handwriting OCR MCP Server
The MCP server for handwritten OCR, providing functions such as document upload, status check, and text retrieval
rating : 2.5 points
downloads : 6.2K
What is the Handwriting OCR MCP Server?
The Handwriting OCR MCP Server is a bridge service that allows various applications to interact with the Handwriting OCR API through the Model Context Protocol (MCP). This service can convert handwritten documents or images into editable digital text (in Markdown format).How to use the Handwriting OCR MCP Server?
Using this service requires three basic steps: 1) Install the server software. 2) Configure the API key. 3) Send documents for recognition through a supported client (such as Claude Desktop).Applicable scenarios
It is suitable for scenarios where handwritten notes, documents, or tables need to be digitized, such as students organizing class notes, enterprises processing handwritten forms, and researchers transcribing historical manuscripts.Main Features
Document Upload
Supports uploading images (JPG/PNG) and PDF documents for handwritten recognition
Status Query
Query the document processing status in real - time to understand the recognition progress
Text Extraction
Return the recognition results in Markdown format, retaining the original format
Advantages
High - precision handwritten recognition technology
Supports multiple document formats (PDF/images)
Seamlessly integrated with the MCP ecosystem
Results are returned in an easy - to - use Markdown format
Limitations
Requires an internet connection to call the cloud API
The recognition accuracy of complex handwritings may decrease
Free accounts have usage limits
How to Use
Install the Service
Automatically install through Smithery or manually configure it into an MCP - supported client.
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Get an API Key
Register an account on the Handwriting OCR platform and obtain an API token.
Configure the Service
Set necessary parameters such as API_TOKEN in the client configuration file.
Use the Service
Upload a document through the client and wait for the processing to complete to obtain the recognition results.
Usage Examples
Digitize Student Notes
Take a photo of handwritten class notes and upload them to convert them into searchable and editable digital notes.
Transcribe Historical Archives
Process scanned ancient handwritten documents to assist historical research.
Frequently Asked Questions
Do I need programming knowledge to use this service?
What is the recognition accuracy?
Which languages are supported for handwritten recognition?
How long does the processing take?
Related Resources
Handwriting OCR Official Website
Service homepage, including registration and API management
API Documentation
Detailed API interface descriptions and technical parameters
GitHub Issue Feedback
Submit issues or feature requests encountered during use
MCP Protocol Introduction
Learn more about the Model Context Protocol
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