MCP server that converts file contents into compact, line-numbered PNG images for vision models to read, reducing token usage by roughly 7x for large files.
An MCP server that provides local image recognition on macOS, including OCR, image classification, comprehensive image analysis, and screenshot recognition, all via Apple's Vision framework without any network requests.
Provides image recognition capabilities using Anthropic Claude Vision and OpenAI GPT-4 Vision APIs, supporting multiple image formats and offering optional text extraction via Tesseract OCR.
A Model Context Protocol server that gives AI assistants OCR with first-class accuracy handling and evaluation. It wraps three engines behind one interface and can score and compare them.
Extracts text from images using Tesseract OCR with support for local files, URLs, and raw image bytes. It provides production-grade OCR capabilities and multi-language support through the Model Context Protocol.
Identifies anime characters and works from illustrations, and traces back to Pixiv originals, artists, or animation screenshots using vision models and SauceNAO/Trace.moe.
Exposes local Umi-OCR v2 capabilities to AI agents via MCP, enabling image text extraction, batch OCR, PDF OCR, and status checks without manually starting the service.
Enables AI agents to recognize and extract text from images using PaddleOCR, supporting both file paths and base64 input with structured results including confidence scores and text positions.
Extracts text content from PDFs and images using Mistral's OCR API, enabling OCR capabilities in MCP-compatible clients like Cursor and Claude Desktop.
Enables text extraction from images and PDF files using the ZhipuAI GLM-OCR API. It allows users to process documents through local file paths or base64-encoded data for high-quality OCR results.
Enables OCR processing of local files and public URLs using Mistral OCR. Provides tools for health checks, key management, page listing, and generating Markdown output.