Canvas Cowork: Turn Your AI Agent into a Visual Collaborator

AI agents are powerful, but their work disappears into terminal logs. Canvas Cowork changes that. It transforms output from leading AI agents — Claude Code, Codex, OpenClaw, and 30+ others — into a shared, visual, multimodal canvas workspace where context, process, and results are easy to follow, trace, and build on.

Generate images, text, video, and Neo agent outputs in a single workflow. Scale creative production through high-efficiency batch generation. Collaborate continuously with teammates on the same canvas.

What Makes Canvas Cowork Different

• Built for shared collaboration — Share a canvas with teammates so they, or the agents they use, can continue, refine, and build on the same work together
• Multimodal by design — Generate images, text, video, and Neo agent outputs in one connected workflow
• High-efficiency batch generation — Agents can fan out work to subagents for batch image and video generation, making large-scale exploration and production much faster
• Visual context management — Instead of losing context in long agent threads, Flowith Canvas organizes work as visible nodes and branches, making creative progress easier to track and manage
• Node-based iteration and traceability — Build through chains, branches, and variations, with clear visual history for comparison, backtracking, and reuse
• Cross-canvas recall — Search past canvases and pull in previous work without interrupting the current flow
• Rich media controls — Support image-to-image, image-to-video, aspect ratio, resolution, duration, loop, and audio settings
• Live shared presence — Work appears directly on the shared canvas in real time, so teammates can see progress, outputs, and structure as it develops

How It Works

Canvas Cowork communicates with Flowith through a WebSocket bridge. Your agent sends commands from the terminal; the canvas in your browser executes them and returns results.

Terminal (Agent) ←→ WebSocket ←→ Browser (Flowith Canvas)

No server to deploy. No API keys to configure. The skill authenticates through a browser handshake — it opens your Flowith tab, confirms the connection, and starts working.

Thinking in Trees

The canvas is not a flat list. It is a tree. Every node can chain, branch, or fork:

# Chain: push a result further
bun $S --bot claude-code submit "refine the color palette" --follow <parentId>

# Branch: explore alternatives from the same point
bun $S --bot claude-code submit "try warm tones" --follow <parentId>
bun $S --bot claude-code submit "try cool tones" --follow <parentId>

This maps directly to how creative work actually happens. You try something, then either push it further or explore a different direction. The canvas preserves the full history.

Batch First

Canvas Cowork is designed around parallel execution. Independent prompts should never be submitted one by one:

# Parallel — fast
bun $S --bot claude-code submit-batch \
  "golden retriever" "husky" "corgi" "poodle"

Four images generated at once. Compare all four side by side before choosing a direction.

Multi-Agent Support

Multiple agents can work on the same canvas simultaneously. The --parallel flag enables read-only session mode for subagents:

bun $S --bot claude-code --parallel --canvas <convId> \
  submit "hero section copy" --wait

Subagents work independently without stepping on each other. Each has its own cursor on the canvas.

Works With All Leading AI Agents

Claude Code · Codex · OpenClaw · Cursor · Windsurf · Cline · Roo Code · Goose · Gemini CLI · GitHub Copilot · OpenCode · Kilo Code · Trae · Junie · Continue · Kiro CLI · and more.

30+ agents supported through the open Skills standard.

Get Started

Open Flowith in your browser, then ask your agent to create a canvas and start generating. Thirty seconds from install to your first image on canvas.

Requirements:

• A Flowith account with an active browser session
• Bun runtime installed

Open source under MIT. GitHub.