AI Tool

Juggler Review

Juggler is a visual workbench for AI coding agents that allows users to run coding sessions locally or remotely, featuring persistent conversation trees and supporting various AI providers through a unified interface.

shipped Sep 14, 2026agentsfree

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Why it matters

1Juggler is a free and open-source visual workbench for AI coding agents.

2It supports multiple AI providers including Claude Code, OpenAI, GitHub Copilot, Gemini, and Mistral.

3The tool features an editable session tree (CRDT) for branching sub-threads and inspecting agent actions.

4Juggler has a context window of 1,048,576 tokens and supports open_standard function calling.

About Juggler

Business Model

Freemium SaaS

Platforms

Desktop (macOS, Windows, Linux)

Target Audience

Developers and creators working with AI coding agents

Pricing Plans

Free

• Download and launch the desktop app
• No Juggler account required
• Open-source core

Leadership

Julian StorerLinkedIn

GitHubOpen Source

Screenshots

overview

What is Juggler?

Juggler is a visual workbench for AI coding agents developed by Julian Storer that enables developers and creators to run and manage AI coding sessions locally or remotely. It features persistent conversation trees and supports various AI providers through a unified interface, offering granular control and deep inspection capabilities over an LLM's actions within codebases. Launched around July 2026, Juggler functions as an open-source graphical user interface (GUI) coding agent, transforming the typical chat-log experience into a navigable, editable document-like session. Its architecture allows for debugging complex agent runs, comparing different agent-generated solutions, and facilitating remote coding sessions by connecting to a headless server.

features

Key Features of Juggler

Juggler provides a comprehensive set of features designed to enhance the interaction and control developers have over AI coding agents. Its core design emphasizes visual representation, editability, and extensibility, moving beyond traditional linear chat interfaces for LLM interactions.

Visual GUI Workbench: Offers a rich graphical interface for interacting with AI coding agents, moving beyond command-line interfaces.
Editable Session Tree (CRDT): Sessions are represented as a Yjs CRDT tree, allowing for branching into sub-threads, recursive drilling down, backtracking, editing, and undo/redo functionality.
Inspectable Everything: Users can inspect tool calls, approvals, and the raw context JSON sent to the LLM.
Multi-Client Architecture: Runs as a local web server, allowing multiple clients (native desktop app, browser tab, or phone) to attach to and synchronize with a live session, enabling remote operation.
Plugin-First Design: Almost every aspect, including context items (read/write/bash), LLM loop strategies, slash commands, and their UIs, are implemented as JavaScript plugins.
"No Electron" Build: Built with Go and Wails, resulting in a single, self-contained binary, avoiding the bloat and dependencies often associated with Electron-based applications.
Read-Only Mode: Includes a "READ ONLY" mode that sandboxes file writes to zero, providing a conservative approach to approving LLM tools and exploring codebases safely.
Persistent Conversation Trees: Maintains conversation history and structure across sessions.
Unified Interface for AI Providers: Supports various LLM providers including Claude Code, OpenAI, GitHub Copilot, Gemini, Mistral, Z.ai, Ollama, and Deepseek.

use cases

Who Should Use Juggler?

Juggler is primarily designed for developers and creators who require granular control and deep inspection capabilities when working with AI coding agents. Its features cater to specific needs in debugging, collaboration, and iterative development with LLMs.

Developers debugging complex agent runs: The visual session tree helps identify where a run branched or an erroneous tool call originated.
Teams requiring remote coding sessions: Users can run the agent on the machine with the code and execution environment, then connect remotely via desktop app or browser.
Developers comparing agent paths: Branching a session before model commitment allows for inspection and comparison of different agent-generated solutions.
Curious power users: Individuals interested in the alpha/beta stage of open-source AI tools who value hands-on control and transparency over LLM thought processes.

how to use

How to Use Juggler

To begin using Juggler, users typically download the native desktop application and configure their preferred AI provider API keys. The tool operates as a local web server, allowing flexible access.

1Download and install the native desktop application for macOS, Windows, or Linux from juggler.studio.
2Configure API keys or access tokens for desired LLM providers such as Claude Code, OpenAI, or Gemini within the Juggler interface.
3Initiate a new coding session, which will be represented as an editable tree structure.
4Interact with the AI coding agent, observing its actions, tool calls, and context JSON within the visual workbench.
5Utilize branching features to explore alternative agent paths or revert to previous states in the session tree.
6Run coding sessions locally or connect remotely to a headless Juggler server running on a different machine.

pricing

Juggler Pricing & Plans

Juggler operates on a freemium-SaaS business model, with its core functionality being free and open-source under the AGPLv3 license. Users are responsible for providing their own API keys or subscriptions for the large language model providers they integrate with Juggler.

Free: Access to the full Juggler visual workbench, persistent conversation trees, and multi-provider support. Users must supply their own LLM API keys.

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Pros

+Provides granular control and deep inspection capabilities over LLM actions within codebases.
+Features an editable session tree (CRDT) allowing for branching, backtracking, and detailed inspection of agent runs.
+Supports a wide range of AI providers including Claude Code, OpenAI, GitHub Copilot, Gemini, and Mistral.
+Multi-client architecture enables remote coding sessions and synchronized access from various devices.
+Built with Go and Wails, resulting in a lightweight, self-contained binary without Electron dependencies.
+Open-source under AGPLv3, fostering community contributions and transparency.

Cons

−Currently described as being in an alpha or beta stage, potentially indicating evolving features and stability.
−Requires users to bring their own API keys or subscriptions for LLM providers, incurring separate costs.
−More suitable for 'curious power users' than teams requiring fully established vendor support and rollout paths.
−Focus on coding agents may be too specialized for users seeking broader AI agent development or orchestration tools.

Similar Tools

Juggler vs Competitors

Juggler differentiates itself in the AI coding agent landscape by focusing on a visual, editable session tree rather than a linear chat log, providing developers with enhanced control and transparency over LLM interactions. This approach contrasts with tools that prioritize broader agent orchestration or low-code application building.

SuperAGIOn Stork

Provides a GUI for building, deploying, and running autonomous AI agents, with a focus on agent orchestration and tool management.

While SuperAGI excels at general autonomous agent creation and management, Juggler is more specifically tailored as a visual workbench for *coding* agents, potentially offering more integrated coding environment features. SuperAGI focuses on broader agent autonomy rather than interactive coding sessions.

FlowiseAIOn Stork

Offers a low-code, visual drag-and-drop interface for building custom LLM apps, including agents, with support for various models and tools.

FlowiseAI provides a broader visual builder for LLM applications and agents, allowing users to construct complex workflows. Juggler is more narrowly focused on providing a workbench specifically for AI *coding* agents and their execution environment, rather than primarily building the agent's underlying logic.

LangflowOn Stork

A UI for LangChain, allowing users to build and experiment with LLM applications and agents using a visual graph interface.

Similar to FlowiseAI, Langflow is a visual builder for LangChain applications and agents, emphasizing the construction of agentic flows. Juggler, however, is designed as a dedicated workbench for running and managing AI coding sessions with agents, offering more direct control over the coding environment and persistent conversation trees.

OpenDevin↗

Aims to be an open-source alternative to Devin, providing an autonomous AI software engineer that can execute complex coding tasks and interact with a shell, browser, and code editor.

OpenDevin is focused on the autonomous execution of coding tasks by an AI agent, offering a more direct 'AI software engineer' experience where the agent takes the lead. Juggler provides a visual workbench for *users to orchestrate* coding agents, offering more direct control and a persistent conversation tree for interactive sessions.

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