Annotate vs Juggler: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Annotate and Juggler — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Annotate

Free

Record your screen, point and speak — turn the session into a video prompt for Cursor, Claude Code, or Codex.

Point-and-Speak Recording: Capture your screen while drawing and narrating so the agent gets both visual and voice context.
Cursor / Claude Code / Codex Handoff: Drop the session directly into your existing agent — no prompt draft to write.
MCP-Based Delivery: Sends frames and speech through MCP so the agent reads structured context instead of a raw video blob.
Multi-Monitor Capture in One Take: Record app on one display and editor on another together in a single session.
UI Markup Tools: Pen, rectangle, and text annotations mark the exact button or region you mean.
Local-Only Processing: Runs entirely on-device on Apple Silicon — no upload, no login, no cloud.
Fewer Tokens per Change: Structured video prompts reduce token load compared to pasting long written briefs.
Free for Mac: No account, no paid tier — full functionality out of the box.

UI Bug Report to Agent: Record a broken flow, circle the problem, and hand it to Cursor to fix.
Design Review with Coding Agent: Show a Figma-to-code diff on-screen and dictate the required visual tweaks.
Cross-App Debugging: Capture logs in one window and the failing UI in another, then let the agent reason across both.
Refactor Requests: Highlight a specific component in the editor and describe the desired API change verbally.
Onboarding a Junior Agent: Walk through a repo layout on video so Codex has context before making changes.
Privacy-Sensitive Codebases: Prompt an on-device agent about sensitive UIs without any recording leaving the Mac.

Julian Storer

Free

A native desktop workbench for AI coding agents with branching conversation trees, inspectable tool calls and editable context.

Branching Conversation Trees: Fork the session at any point, recursively, so competing approaches and tangents run side by side without polluting the main context.
Miller Column Navigation: A Finder-style column layout lays out tool calls, item properties and nested sub-threads for long reading and editing sessions.
Transaction Inspector: Open any model transaction to see the assembled system prompt, messages, tool definitions, output, token use, timing and stop reason.
The Context Surgeon: Fold history into a new thread, move or copy items between branches, expand a branch back into its parent, and undo structural changes.
Local or Remote Sessions: Run the desktop app locally or the headless binary on the machine holding the code, then attach from the app, a browser or a phone.
Durable Sessions: Sessions are stored on disk as live-synced Yjs documents, so quits, relaunches and dropped connections do not lose the conversation.
Automatic Context Sizing: Juggler measures the full request before each call, reserves room for the answer and compacts older history before limits become an error.
Inspectable MCP Tools: Follow an MCP handoff end to end - schema offered, arguments generated, approval, result and errors - with server status, logs and per-tool filtering.
JavaScript Extension SDK: Context items, LLM loop strategies, slash commands, viewers and Pinboard tabs are extensions you can fork or replace, under a permissive Apache-2.0 SDK.

Exploring Competing Fixes: Branch a thread into two sub-threads to try different approaches to the same bug and compare results before committing.
Auditing Agent Behavior: Inspect exactly what the model received and returned when an agent makes a surprising edit to the codebase.
Remote Development: Run the server on a dev box or GPU machine where the repository lives and drive the same live session from a laptop or browser.
Long Refactors: Keep a multi-hour session alive across quits and reconnects, with the agent paused awaiting approval for its next step.
Provider Comparison: Drive Claude Code, Codex, Copilot, Gemini and local Ollama models through one interface to compare behavior on the same task.
Custom Tooling: Write JavaScript extensions that add slash commands, file viewers or new LLM loop strategies to the workbench.