"Optical Character Recognition (OCR) Technology" matching MCP servers:

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

MCP server for intelligent circuit diagram recognition, enabling detection of components, text, topology, and netlist from circuit images.

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.

Exposes ComfyUI-generated character avatars as tools, allowing control of expressions and poses via preset workflows with adjustable parameters.

Enables MCP clients to run OCR on local image files through a single long-lived PaddleOCR backend shared across clients, returning recognized lines as a Markdown table with optional coordinate and confidence columns.

A local MCP server that drives one disposable copy of VRoid Studio through the application's own managed API, exposing 86 tools for character parameters, textures, bounded makeup editing, hair authoring, Dress-up outfit assembly, and VRM export without mouse automation, OCR, or screen scraping. It also verifies installations into an isolated lab directory and guards the copy against writes outside that lab.

Provides detailed character analysis for text, counting total characters, characters without spaces, letters, numbers, and symbols through a simple MCP tool interface.

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.

Enables OCR-enabled PDF to Markdown conversion in Claude Code, with per-page inspection and hybrid handling of text, scanned, mixed, and blank pages via a local vision-model endpoint.

Provides structured OCR with verified bounding boxes using the space-ocr API. Allows extraction of structured fields from document images and listing of built-in templates.

Enables AI agents to convert images and PDFs, including large scanned books, into Markdown through GLM-OCR, with support for long-image slicing, progress tracking, and asynchronous OCR tasks.

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.

Gives vision-less LLMs the ability to recognize clipboard screenshots and images by proxying to an OpenAI-compatible vision model.

Enables users to create character spritesheets from natural-language requests, preview animations, search clothing and tool items, and export engine-ready assets for Godot, Unity, and web.

A lightweight server that provides detailed text analysis, counting total characters, characters without spaces, letters, numbers, and symbols for AI assistants like Claude Desktop and GitHub Copilot.

Gives coding agents on-device OCR that turns images, PDFs and scans into Markdown with tables, plain text or JSON. Also fills a JSON Schema from a document using a local language model, with all processing kept on the machine.

Enables document text recognition and extraction from images and PDFs using Claude Vision, including support for scanned documents and structured output, without requiring local OCR engines.

High-performance OCR server using native Tesseract (C++) for text extraction from images, integrable with ChatGPT Desktop and other MCP clients.

Identifies anime characters and works from illustrations, and traces back to Pixiv originals, artists, or animation screenshots using vision models and SauceNAO/Trace.moe.

Provides an OCR tool that extracts text from images using macOS's built-in Vision framework, returning text segments with confidence scores and bounding boxes.