Catenary
Catenary is a local-first spatial IDE that orchestrates AI coding agents (Claude Code, Codex, Cursor, Grok, OpenCode, Pi, etc.) on an infinite canvas, combining floating terminals, Monaco editors, browsers and isolated git worktrees with visual wires and a side-by-side editor for tracking agent activity.
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Quick Overview
Best for: AI Agents
What it does
AI Tools software for decision-makers comparing workflow fit and alternatives.
Best fit
AI Agents
Pricing snapshot
Freemium from US$ 0
Next step
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Catenary
Catenary is a spatial IDE that lets developers run and orchestrate multiple AI coding agents simultaneously on a single infinite canvas. Panels such as terminals, Monaco editors, browsers and parallel git worktrees float on the canvas so you can pan, zoom and arrange agent work visually while watching each agent operate. It is local-first: there is no account, no telemetry, and your API keys and code remain on your machine. Catenary targets developer workflows — providing isolated worktrees for experiments, git-aware diffs, context wires to relay data between agents, and a Maestro mode to recruit and coordinate helper agents.
Spatial canvas IDE for AI coding agents Discussion | Link
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Claim this listing for $29Key Features
Infinite Canvas with Floating Panels
Terminals, Monaco editors, browsers and parallel git worktrees float on one infinite canvas. You can pan, zoom and arrange every agent and view them working in parallel.
Isolated Worktrees & Branches
One-click creation of isolated branches and worktrees per task/agent so experiments do not touch your main working tree; each task gets a color and its own state in the sidebar and canvas.
Monaco Editor with Side-by-Side Diffs
Includes VS Code's Monaco editor inside the canvas with a side-by-side diff view showing exactly what an agent changed; the file tree is git-aware.
Context Wires
Drag wires to send context between panels and agents; wires can relay automatically or act as permissions so downstream agents receive only requested context.
Maestro Mode
One agent can recruit, brief and wire a team of helpers (default up to five, adjustable up to ten). Actions are gated by editable approval cards before changes appear on the canvas.
Multi-project & Parallel Branches
Each open project has its own canvas; tasks run in isolated worktrees with their own agent so multiple projects and branches can run in parallel without cross-contamination.
Local-first Privacy & Offline Guarantees
Catenary keeps code and keys local, sends zero bytes of source code or terminal output to remote servers, and documents outbound traffic (two hosts) and what it never sends.
Pricing
Full-featured local installation at no cost with limitations on parallel tasks and Maestro helpers; no account or telemetry required.
Free
US$ 0- Canvas, terminals, editor, browser, git
- Unlimited connection wires
- Unlimited projects open at the same time
- 1 parallel tasks
Pro (Lifetime, launch price)
US$ 19 (launch); standard price after launch US$ 29- Canvas, terminals, editor, browser, git
- Unlimited connection wires
- Unlimited projects open at the same time
- Unlimited parallel tasks
Use Cases
Parallel experimentation
Run multiple experiments or branches at once in isolated worktrees and visually compare results without affecting your working tree.
Agent-assisted refactoring and fixes
Recruit agents to perform refactors, fix performance issues (e.g., N+1 queries) and review or apply suggested changes with side-by-side diffs before accepting them.
Coordinated multi-agent workflows
Use Maestro mode to brief and wire teams of helper agents that organize themselves while you approve actions, enabling complex delegated workflows.
Privacy-preserving AI integrations
Run agents that use your own API keys (Anthropic, OpenAI, Google, local runtimes) so prompts and keys are not routed through a third party.
Integrations
Anthropic (Claude)
Orchestrate agents using Claude-backed models with your own API key.
OpenAI (Codex and other models)
Connect to OpenAI models using your API key for agent functionality.
Google models
Use Google-hosted models via your own credentials for agent tasks.
Ollama / LM Studio (local runtimes)
Point agents at local LLM runtimes so model inference can run entirely on your machine.
Git & GitHub Releases
Git-aware file tree and update-checks via a GitHub Releases file (used to check for new versions).
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Download the appropriate build for your OS from the site (Windows, macOS Apple Silicon/Intel, Linux AppImage/.deb/.tar.gz).
- 2 Run the installer; note the HEADS UP that the installer is not code-signed yet and the OS may block it on first run — follow the docs for the two-click allowance.
- 3 Launch the app and create a New Task to spawn an isolated worktree, branch and agent, or use Maestro to recruit helpers.
- 4 Configure your preferred agent/LM by supplying your own API key or pointing to a local runtime (Ollama, LM Studio) — keys are kept local.
Support
Report bugs or request support via [email protected] (listed on the site footer).
docs
Documentation and installation guidance linked from the product site (Docs link on https://thecatenary.app/).
releases
Download and update information via GitHub Releases (github.com/GioNicolas/catenary-releases).
API
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