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

Provides a tool to count occurrences of specific characters in text, serving as a simple example of building MCP servers with FastMCP and Python.

Enables AI clients to create, edit, run, and inspect ScratchJr Desktop projects using natural language, including characters, backgrounds, text, sounds, and programming blocks.

An MCP server that implements iterative refinement of responses through self-critique cycles, breaking the process into discrete steps to avoid timeouts and show progress.

Archive Agent is an open-source semantic file tracker with OCR + AI search (RAG) and MCP capability.

An MCP server that implements a conversational AI 'waifu' character using a text generation service with Redis queuing and GPU acceleration.

Enables an MCP client to connect to a running Blockland client to execute TorqueScript, inspect player state, control character movement and actions, and capture screenshots.

Calculates optimal chunk offsets for large files to bypass Claude Code's 50K character truncation limit while maintaining native Read/Edit/Write compatibility. It allows the AI to seamlessly re-read files in correctly-sized pieces by providing a specific reading plan.

A multi-model platform that integrates RAG (Retrieval-Augmented Generation) with LLMs, supporting OCR via Tesseract and offering both backend API and frontend web interface.

An MCP server for interacting with Saptiva AI's suite of models, offering capabilities such as chat completions, chain-of-thought reasoning, and OCR. It enables users to generate semantic embeddings, access specialized prompts, and manage AI-driven workflows through a standardized interface.