Snip

Snip

Screenshot and diagram tool for AI agents. Capture and annotate screenshots to show Claude what you mean — or let the agent render Mermaid diagrams and open them for visual review. Approve, annotate, or request changes with text feedback. Built-in review mode with structured responses. CLI and MCP server for Claude Code, Cursor, Windsurf, Cline. macOS, open source, free.

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README

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Snip

snipit.dev

Visual communication layer between humans and AI agents for macOS.

Capture and annotate screenshots, render diagrams from code, review agent-generated visuals with approve/request-changes flow — all from the menu bar. AI organizes and indexes everything for semantic search. CLI and MCP integration let any AI agent use Snip as their visual I/O.

Install

brew install --cask rixinhahaha/snip/snip

Or download the DMG directly from Releases (Apple Silicon only).

Quick Start (Development)

npm install
npm run rebuild   # compile native modules
npm start         # launch (tray icon appears in menu bar)

Requires macOS 14+, Node.js 18+, and Xcode CLT (xcode-select --install). macOS 26+ recommended for native Liquid Glass effects.

For AI-powered organization, install Ollama separately. Snip detects your system Ollama and guides you through setup in Settings.

How It Works

  1. Cmd+Shift+2 — Fullscreen overlay appears on whichever display the cursor is on, drag to select a region
  2. Annotate — Rectangle, arrow, text, tag, blur brush, or AI segment tools
  3. Esc — Copies annotated screenshot to clipboard
  4. Cmd+S — Saves to disk + AI organizes in background

Screenshots saved to ~/Documents/snip/screenshots/. AI renames, categorizes, and indexes them for search.

Agent Integration (CLI & MCP)

Snip exposes a CLI and MCP server so AI agents can use it as their visual I/O:

# Render a Mermaid diagram and open for review
echo 'graph LR; A-->B-->C' | snip render --format mermaid --message "Does this flow look right?"

# Open an image for agent review
snip open screenshot.png --message "Is the layout correct?"

The agent gets structured feedback: { status: "approved" | "changes_requested", edited, path, text? }. The user can annotate spatially, type text feedback, or just approve.

MCP tools: render_diagram, open_in_snip, search_screenshots, list_screenshots, get_screenshot, transcribe_screenshot, organize_screenshot, get_categories, install_extension.

Key Shortcuts

Shortcut Action
Cmd+Shift+2 Capture screenshot
Cmd+Shift+1 Quick Snip (select & copy to clipboard)
Cmd+Shift+S Open semantic search
Cmd+S Save to disk (in editor)
Esc / Enter Copy to clipboard & close (in editor)
V / R / T / A / G / B / S Select / Rectangle / Text / Arrow / Tag / Blur / Segment tools
U Upscale image
W Transcribe text

Documentation

Doc Role Contents
docs/PRODUCT.md Product Manager Vision, feature specs, terminology, product principles
docs/DESIGN.md Designer Color palettes (Dark/Light/Glass), component patterns, glass effects, icon specs
docs/ARCHITECTURE.md Developer Code structure, conventions, IPC channels, data flow, key decisions
docs/DEVOPS.md DevOps Build pipeline, signing, native modules, environment setup
docs/USER_FLOWS.md QA / PM Detailed user flows for every feature, edge cases, test cases
CLAUDE.md Claude Code Autonomous agent instructions, role references, documentation rules

Tech Stack

Electron 33 / Fabric.js 7 / Mermaid.js 11 / Ollama (local LLM) / HuggingFace Transformers.js / SlimSAM (ONNX) / Chokidar 4 / electron-liquid-glass

On-Device Models

All AI runs locally — no cloud APIs needed for core features.

Model Purpose By Link
MiniCPM-V Vision LLM (naming, tagging, categorizing) OpenBMB HF
SlimSAM-77-uniform Object segmentation Meta AI / Xenova HF
Swin2SR-lightweight-x2-64 Image upscaling (2x) Conde et al. / Xenova HF
all-MiniLM-L6-v2 Semantic search embeddings Microsoft / Xenova HF
Vision OCR Text transcription Apple Built into macOS

License

MIT

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