Macos Vision Mcp

Local OCR & screen understanding for agents: read any window, find what to click. No uploads.

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LLM Mart 4 views 11 listing impressions
Transport
Not stated
Package
—
Registry id
io.github.woladi/macos-vision-mcp

No install snippet on purpose. A working MCP config is a command, its arguments and an environment block — the last two are where API keys live, so this catalogue never stores them and cannot publish them. Follow the link above for the authors' own instructions.

Local, private, offline OCR and UI testing for any MCP client — no API keys, no uploads. Cut document token costs by ~97%, and let an agent see and click your Mac's UI without a single screenshot leaving the machine.

npm version npm downloads GitHub stars License: MIT macOS 13.0+ No API Key Offline Glama

Pre-extracts text and image data locally before your AI ever sees it — cutting token usage by ~97% on real documents and returning structured paragraphs, lines, and bounding boxes so the model can reconstruct the document into Markdown, HTML, DOCX, or any other format. Files never leave your Mac: no cloud API, no API keys, no network requests.

How the ~97% is measured: a 44-page scanned PDF sent as page images costs ~73,500 tokens; the same file run through analyze_document returns ~2,400 tokens of extracted text and structure (raw page-image tokens vs. extracted-text tokens). Your numbers vary with page density and tokenizer — treat 97% as the order of magnitude, not a guarantee.

Contents: Quick Start · What you get · What agents use this for · UI testing · Why it's different · Available Tools · Usage · Example workflows · Configuration · Privacy layer

What you get

  • OCR for images and PDFs (JPG, PNG, HEIC, TIFF, multi-page PDF) via Apple Vision Framework.
  • ~97% token reduction: a 44-page PDF costs ~2,400 tokens instead of ~73,500.
  • Reading-order paragraphs + raw text blocks with bounding boxes — rich structure for the model to reconstruct the document into any output format (Markdown, HTML, DOCX, JSON), not a lossy plain-text dump.
  • Face detection, barcode/QR reading, and image classification — all on-device.
  • Full document pipeline: OCR + faces + barcodes + rectangles in a single tool call.
  • Works with Claude Code, Claude Desktop, and Cursor — any MCP-compatible client.
  • No files uploaded to any server — processing stays entirely on your Mac.
  • UI testing for agents: screenshot a window locally, find an element by its visible text, get back click coordinates, and assert what's on screen — all without uploading the screenshot.
  • 100% offline after npm install — powered by Apple Vision Framework, same engine as Live Text in Photos.app.

❌ Without / ✅ With

❌ Without macos-vision-mcp:

  • Sending a 44-page PDF costs ~73,500 tokens
  • Every image, invoice, or contract goes through a cloud API
  • Sensitive documents leave your machine on every request

✅ With macos-vision-mcp:

  • Local Apple Vision pre-extracts text before Claude ever sees it
  • ~2,400 tokens for the same 44-page PDF — 97% fewer
  • Files never leave your Mac

What agents use this for

From the project's README.