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OpenAI OCR MCP Server

OpenAI OCR MCP Server

Local
github.com/cjusAI & Agents5Updated 79w ago
Repository

About OpenAI OCR MCP Server

OpenAI OCR MCP Server extracts text from images using OpenAI vision and saves the result as a text file. It is for users processing image text in Cursor, with support for several common image formats.

Key features

  1. 01Extract image text with GPT-4.1-mini
  2. 02Create text files beside source images
  3. 03Name files using content hashes
  4. 04Support JPG, PNG, GIF, and WebP
  5. 05Validate file size and report errors

Use cases

  1. 01Extract readable text from document images
  2. 02View OCR results in Cursor
  3. 03Save extracted text alongside its source image

MCP support

This MCP server exposes an image OCR tool to clients such as Cursor. Clients can submit an image and receive extracted text; the server also saves a text file beside the image.

Configuration

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

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

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

OpenAI OCR MCP Server

A Model Context Protocol (MCP) server that provides OCR (Optical Character Recognition) functionality using OpenAI's vision capabilities. This server integrates with Cursor IDE to provide seamless text extraction from images.

Features

  • Image Text Extraction: Extract text from various image formats using OpenAI's GPT-4.1-mini vision model
  • Automatic Text File Creation: Automatically saves extracted text alongside the source image
  • Content-Based File Naming: Uses unique content hashing for organized file management
  • Multiple Image Format Support: Supports JPG, PNG, GIF, and WebP formats
  • Robust Error Handling: Comprehensive validation and error reporting
  • Detailed Logging: Debug-friendly logging for troubleshooting

Technical Details

Vision Model
  • Uses OpenAI's GPT-4.1-mini model
  • Optimized for text extraction from images
  • Supports high-detail image analysis
  • Processes images through OpenAI's vision API
File Processing
  • Automatic text file creation
  • Content-based hash generation
  • Support for multiple image formats
  • Built-in file size validation

Installation

  1. Clone the repository
  2. Install dependencies: 
    npm install
  3. Build the TypeScript code: 
    npm run build
  4. Set up your OpenAI API key in a .env file: 
    OPENAI_API_KEY=your_api_key_here

Usage

In Cursor IDE
  1. Configure the MCP server in your Cursor settings
  2. Use the OCR tool through Cursor's command palette
  3. Select an image file to process
  4. The extracted text will be:
    • Displayed in Cursor
    • Saved as a text file next to the image
Text File Output

For each processed image, the server creates a text file with the following naming convention:

{original_image_name}-{content_hash}.txt

Example:

  • Input image: document.jpg
  • Output file: document-a1b2c3d4.txt

The content_hash is a unique 8-character hash generated from the extracted text, ensuring:

  • Unique filenames for different text content
  • Easy matching between source images and extracted text
  • Version tracking when the same image produces different results
Supported Image Formats
  • JPEG/JPG
  • PNG
  • GIF
  • WebP
File Size Limits
  • Maximum file size: 5MB
  • Files exceeding this limit will be rejected with an error message

Error Handling

The server provides detailed error messages for common issues:

  • Invalid image formats
  • File size exceeded
  • File access problems
  • API key issues
  • Text extraction failures

Development

Building from Source
npm run build
Running Tests
npm test
Debugging

The server provides detailed logs including:

  • API key validation
  • File processing steps
  • Text extraction results
  • File saving operations

Environment Variables

  • OPENAI_API_KEY: Your OpenAI API key (required)
  • Supports both standard (sk-...) and project-specific (sk-proj-...) API keys

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Comments

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From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.