Working with AI agents

noodlelab is built to be used by coding agents as much as by people. An agent gets the same discipline a person does (units on every number, uncertainty on every measured input, requirements checked with margins, a record of every run) and you get work you can review instead of work you have to trust.

There are three ways in:

• The MCP server, noodlelab mcp. Add it to Claude Code, Codex CLI or any MCP client and the agent can find nodes, build and edit graphs, run them and verify the result. The MCP tools lists every tool.

• The Python library, noodlelab.verify, for agents that write scripts, notebooks and tests. Quickstart has a verified calculation in ten lines.

• The Agent panel in the editor, which runs Claude Code or Codex CLI in a terminal under the canvas, already connected to the MCP server.

Whichever it uses, the agent is done when noodlelab verify --json exits 0.

To set up a project for agents, run noodlelab init-agent: it writes the instructions, a skill and .mcp.json. Adopting noodlelab in a project is the step-by-step, and the guide for agents is what the agent reads first.