What vision model does the server use?
It uses OpenAI’s GPT‑4.1‑mini model, optimized for text extraction from images with high‑detail analysis.
@cjus
Basic information
OpenAPI (based) text from image extraction MCP Server
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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OpenAI OCR MCP Server is a Model Context Protocol (MCP) server that uses OpenAI’s GPT‑4.1‑mini vision model to extract text from images. It integrates with Cursor IDE, allowing users to select an image file and receive the extracted text directly in the IDE, as well as saved as a separate text file.
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.
It uses OpenAI’s GPT‑4.1‑mini model, optimized for text extraction from images with high‑detail analysis.
The server supports JPEG/JPG, PNG, GIF, and WebP formats.
Yes, images must be 5MB or smaller; larger files are rejected with an error message.
The text file follows the pattern `{original_image_name}-{content_hash}.txt`, where the hash is an 8‑character unique identifier derived from the extracted text.
Yes, a valid OpenAI API key (either standard `sk-...` or project‑specific `sk-proj-...`) must be set in the `OPENAI_API_KEY` environment variable.
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