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

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

Juggler

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.

Proteus Computer Use

Freemium

Local-first macOS screen recorder that captures, labels, and indexes team workflows so knowledge stays searchable and private.

Local-First Capture: Recordings live in ~/.screencap on your Mac and never leave unless you explicitly share them.
On-Device Task Segmentation: An on-device model breaks long recordings into labeled tasks like payroll runs, expense approvals, or CRM data entry.
Full-Text Search of Workflows: Every spoken word and on-screen moment is indexed so any past workflow can be surfaced months later by search.
Privacy-Enforced Recording: Password managers and banking apps are cut before a frame is written; email and chat are masked in real time.
MCP Context Snapshots: While recording, Screencap queries connected MCP servers to capture the exact Gusto/Attio/Linear/Notion record on screen inside the video.
Deliberate Sharing With PII Scrubbing: Every shared copy is scrubbed of names, secrets, and PII, and only the recordings you pick ever leave the machine.
Source-Available Codebase: The full capture engine, encryption, agent, and anonymizer are public on GitHub under PolyForm Noncommercial 1.0.0.

Team Onboarding: Assemble ordered collections of real workflow recordings so new teammates learn exactly how work is actually done.
Institutional Knowledge Capture: Preserve the tacit steps behind payroll runs, reconciliations, and quarterly reports as searchable video.
Ops Documentation: Replace stale wikis by pointing teammates at labeled task recordings that stay current with the real system.
Compliance-Sensitive Recording: Capture back-office work in banking, finance, and HR without leaking passwords, account balances, or PII.
Computer-Use Dataset Contribution: Optionally donate reviewed, scrubbed recordings to a public dataset for training open computer-use models.