OpenAI OCR MCP Server
About
OpenAPI (based) text from image extraction MCP Server
Details
- Author
- cjus
- GitHub stars
- 5
- Downloads
- 207
- Categories
- AI
Jump to
- Text extraction from images via OpenAI’s GPT‑4.1‑mini vision model.
- Automatic creation of text files alongside the source image.
- Content‑based file naming using a unique 8‑character hash.
- Supports JPEG, PNG, GIF, and WebP image formats.
- Robust error handling with detailed, debug‑friendly logging.
Install dependencies (npm install), build the TypeScript code (npm run build), and set the OPENAI_API_KEY environment variable in a .env file. In Cursor IDE, configure the MCP server, then use the OCR tool via the command palette to select an image file. The extracted text is displayed in Cursor and automatically saved as a text file next to the source image.
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 APIFile Processing
- Automatic text file creation - Content-based hash generation - Support for multiple image formats - Built-in file size validationInstallation
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
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