$ loading_
Let AI agents run local Umi-OCR for image and PDF text extraction.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Umi-OCR MCP Server" yet — see the docs or source repo.
Use the Umi-OCR MCP Server to extract all text from this screenshot and return it in the original paragraph order.
Returns readable text from the screenshot while preserving the original order and structure as much as possible.
Use the Umi-OCR MCP Server to batch process the images in this folder and output OCR results for each file separately.
Returns batch OCR results organized by file for easier follow-up organization or analysis.
Use the Umi-OCR MCP Server to perform OCR on this PDF and produce the full copyable text.
Returns the full extracted text from the PDF for search, summarization, or archiving.
Office workers or researchers can have AI read text from images or PDFs through this MCP tool, avoiding manual transcription. It fits screenshots, scans, and image-based documents.
Developers can expose local Umi-OCR v2 capabilities to AI agents and batch-recognize text from images inside automated workflows. This makes OCR a reusable step in agent pipelines.
When an agent depends on local OCR, it can check the service status before running recognition tasks. This helps reduce workflow interruptions caused by unavailable local OCR capability.
It exposes local Umi-OCR v2 capabilities to AI agents through MCP. Known functions include image text extraction, batch OCR, PDF OCR, and status checks.
Based on the description, one goal is to let AI agents use OCR without manually starting the service. For exact runtime behavior, see the source repository.
Its distinguishing feature is not a standalone user interface, but exposing local Umi-OCR v2 through MCP for direct agent use. In other words, it is better suited for agent-driven and automated workflows.
Enable non-vision agents to describe images, run OCR, and extract structured data.
Use one OCR interface and evaluate multiple recognition engines for AI workflows.
Recognize images, extract text, and return structured JSON or tables.
Convert PDFs into citeable structured content for parsing, extraction, Q&A, and rendering.
Extract and structure key information from PDFs, images, and Office documents.
Extract text from images and PDFs for search, organization, and automation.