Coding Agent
A chat that can see your canvas and act on it — with your choice of model or command-line assistant.
Circuitry's coding agent lives in a chat panel you open beside whatever you're working on. It sees the document in the other pane — a workflow, a design, a code file — and your current selection, so you can point at things and say "this." It can run as Circuitry's own agent or hand the wheel to a command-line assistant like Claude Code, Gemini CLI, or Codex CLI.
Opening the panel
From a workflow or chatflow, click the Agent Chat button (the speech-bubble icon) in the toolbar along the bottom of the canvas. The chat opens in a pane next to your work.
You can also pair a chat with any document by dragging it into a split-screen — the chat becomes an agent the moment it's side-by-side with a workflow, design, or code file. See Agent Chat in Split-Screen.
Two modes
A toggle in the chat header switches between the two:
- Agent — Circuitry's built-in agent. It uses the model you pick, reads your open document and selection, and makes changes through plan approval (it shows you what it's about to do) and diff approval (code edits land as accept/reject hunks). This is the default.
- CLI — runs a command-line coding assistant right inside the panel. Switch to it with the header toggle. CLI mode needs a project folder open and a connected Circuitry Server.
In CLI mode a dropdown lets you pick which assistant to run:
- Claude Code
- Gemini CLI
- Codex CLI
Each shows whether it's installed on the machine running the Circuitry Server; install the ones you want the usual way and they appear here.
Pasting images
Both modes take pictures — a screenshot of a bug, a design reference, a diagram:
- Agent mode — attach an image to your message by pasting or dropping it onto the message box.
- CLI mode — paste, drag-and-drop, or right-click an image straight into the terminal. Use Ctrl+V on macOS or Ctrl+Shift+V on Windows and Linux. See Terminals.
Connecting a command-line assistant to your canvas
A command-line assistant on its own can read and edit files. Connect it to Circuitry and it can also see your canvas — look up a node by name, read what you have selected, create and edit nodes, and round-trip its file edits through diff approval — the same abilities the built-in agent has.
To set this up, install the Circuitry connector (the Model Context Protocol server) once:
npx @circuitry/mcp-server setup
It's also bundled with the Circuitry Server download. After setup, point your command-line assistant at it and ask, in plain English, to work with your canvas — "add a node that…", "read my selection and…".
This is the reverse of the MCP node, which brings an outside tool server into an agent. Here you're exposing Circuitry's tools to an outside assistant.
Models for the built-in agent
The Agent mode has its own model picker. Your options:
- Circuitry cloud models — OpenAI, Anthropic, and Google models, run through Circuitry's server-side keys.
- Command-line models — a connected assistant (Claude Code and friends) can back the agent too, kept alive across messages for fast turns.
- Local models — run entirely on your own machine with LM Studio or Ollama. See Using Local AI Models.
- On-device — Apple Intelligence on Mac and iPad, with nothing leaving the device.
- Your own custom models — add any compatible endpoint.
Choose which models appear in Settings → Models, then pick one per chat from the model dropdown. You can switch models mid-conversation — start cheap, bump to a stronger model for the hard part.
What you can ask it to do
Because the agent sees your canvas and selection, you can work by pointing rather than describing:
- Look things up — "find the node called Fetch Orders" — the agent looks up nodes by name or searches for them.
- Refer to a selection as "this" — select nodes, drawing strokes, spreadsheet cells, or lines of code, then ask about this or tell the agent to change this. Your selection is handed to the agent automatically.
- Code → diagram — "draw a flowchart of the login flow in my code" — it reads the code and lays out a flow on a canvas.
- Diagram → code — "implement this flow" — it reads the diagram and writes the code, landing as diff hunks.
- Design → app — select design elements and ask the agent to integrate them into the app you're building.
- Everything in between — create and connect nodes, run code nodes, edit sheets, generate pages and designs, and search your knowledge base.